Workshop
NeurIPS 2023 Workshop: Machine Learning and the Physical Sciences
Brian Nord · Atilim Gunes Baydin · Adji Bousso Dieng · Emine Kucukbenli · Siddharth Mishra-Sharma · Benjamin Nachman · Kyle Cranmer · Gilles Louppe · Savannah Thais
Hall B2 (level 1)
Fri 15 Dec, 6:15 a.m. PST
Physical sciences and machine learning: more than the sum of their parts. Join us to discuss research at the convergence of these fields!
Chat is not available.
Timezone: America/Los_Angeles
Schedule
|
Fri 6:15 a.m. - 6:30 a.m.
|
Opening remarks
(
Introductory remarks by the organizers
)
>
SlidesLive Video |
🔗 |
|
Fri 6:30 a.m. - 6:55 a.m.
|
Benefits of Approximate and Partial Equivariance
(
Invited talk
)
>
SlidesLive Video |
Shubhendu Trivedi 🔗 |
|
Fri 6:55 a.m. - 7:20 a.m.
|
Interpretable deep learning for protein modeling
(
Invited talk
)
>
SlidesLive Video |
Maria Rodriguez Martinez · Maria Rodriguez Martinez 🔗 |
|
Fri 7:20 a.m. - 8:15 a.m.
|
Panel on inductive biases and interpretability
(
Panel discussion
)
>
SlidesLive Video |
Shubhendu Trivedi · Anuj Karpatne · Joshua Speagle · Savannah Thais 🔗 |
|
Fri 8:15 a.m. - 8:45 a.m.
|
Coffee break
(
Coffee break
)
>
|
🔗 |
|
Fri 8:45 a.m. - 9:00 a.m.
|
Removing Dust from CMB Observations with Diffusion Models
(
Contributed talk
)
>
SlidesLive Video |
David Heurtel-Depeiges 🔗 |
|
Fri 9:00 a.m. - 10:15 a.m.
|
Poster session 1 ( Poster session ) > link | 🔗 |
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Fri 10:00 a.m. - 11:30 a.m.
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Lunch break
(
Lunch break
)
>
|
🔗 |
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Fri 11:30 a.m. - 12:00 p.m.
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What's missing? A speculative sketch of the future of machine learning and science
(
Invited talk
)
>
SlidesLive Video |
Alexander Alemi 🔗 |
|
Fri 12:00 p.m. - 1:15 p.m.
|
Poster session 2 ( Poster session ) > link | 🔗 |
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Fri 1:15 p.m. - 1:30 p.m.
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Coffee break
(
Coffee break
)
>
|
🔗 |
|
Fri 1:30 p.m. - 1:45 p.m.
|
Towards an Astronomical Foundation Model for Stars
(
Contributed talk
)
>
SlidesLive Video |
Henry Leung 🔗 |
|
Fri 1:45 p.m. - 2:00 p.m.
|
KeyCLD: Learning Constrained Lagrangian Dynamics in Keypoint Coordinates from Images
(
Contributed talk
)
>
link
SlidesLive Video |
Rembert Daems 🔗 |
|
Fri 2:00 p.m. - 2:15 p.m.
|
Ultra Fast Transformers on FPGAs for Particle Physics Experiments
(
Contributed talk
)
>
SlidesLive Video |
Elham E Khoda 🔗 |
|
Fri 2:15 p.m. - 3:15 p.m.
|
Panel on institutional support and funding
(
Panel discussion
)
>
SlidesLive Video |
Jesse Thaler · Max Welling · John Wu · Sara Hooker 🔗 |
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Fri 3:15 p.m. - 3:30 p.m.
|
Closing remarks
(
Closing remarks by the organizers
)
>
SlidesLive Video |
🔗 |
|
-
|
Control-aware echo state networks (Ca-ESN) for the suppression of extreme events
(
Poster
)
>
|
Alberto Racca · Luca Magri 🔗 |
|
-
|
KeyCLD: Learning Constrained Lagrangian Dynamics in Keypoint Coordinates from Images
(
Poster
)
>
|
Rembert Daems · · Francis Wyffels · Guillaume Crevecoeur 🔗 |
|
-
|
Incorporating Additive Separability into Hamiltonian Neural Networks for Regression and Interpretation
(
Poster
)
>
|
Zi-Yu Khoo · Jonathan Sze Choong Low · Stéphane Bressan 🔗 |
|
-
|
Extracting an Informative Latent Representation of High-Dimensional Galaxy Spectra
(
Poster
)
>
|
Daiki Iwasaki · Suchetha Cooray · Tsutomu Takeuchi 🔗 |
|
-
|
When Black-box PDE Solvers Meet Deep Learning: End-to-End Mesh Optimization for Efficient Fluid Flow Prediction
(
Poster
)
>
|
Shaocong Ma · James Diffenderfer · Bhavya Kailkhura · Yi Zhou 🔗 |
|
-
|
Physics-consistency of infinite neural networks
(
Poster
)
>
|
Sascha Ranftl 🔗 |
|
-
|
Pay Attention to Mean Fields for Point Cloud Generation
(
Poster
)
>
|
Benno Käch · Isabell Melzer · Dirk Krücker 🔗 |
|
-
|
Simulation-based Inference for Cardiovascular Models
(
Poster
)
>
|
Antoine Wehenkel · Jens Behrmann · Andy Miller · Guillermo Sapiro · Ozan Sener · Marco Cuturi · Joern-Henrik Jacobsen 🔗 |
|
-
|
Fast SoC thermal simulation with physics-aware U-Net
(
Poster
)
>
|
11 presentersYu-Sheng Lin · Li-Song Lin · Chin-Jui Chang · Ting-Yu Lin · Shih-Hong Pan · Ya-Wen Yu · Kai-En Yang · Wei Cheng Lee · Yi-Chen Lin · Tai-Yu Chen · Jason Yeh |
|
-
|
Unsupervised segmentation of irradiation-induced order–disorder phase transitions in electron microscopy
(
Poster
)
>
|
Arman Ter-Petrosyan · Jenna A Bilbrey · Christina Doty · Bethany Matthews · Le Wang · Yingge Du · Eric Lang · Khalid Hattar · Steven Spurgeon 🔗 |
|
-
|
Attention-guided neural differential equations for physics-constrained deep learning of ion transport
(
Poster
)
>
|
Danyal Rehman · John Lienhard 🔗 |
|
-
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Learning Closure Relations using Differentiable Programming: An Example in Radiation Transport ( Poster ) > link | Aidan Crilly · Benjamin Duhig · Nacime Bouziani 🔗 |
|
-
|
DFT Hamiltonian Neural Network Training with Semi-supervised Learning
(
Poster
)
>
|
Yucheol Cho · Guenseok Choi · Gyeongdo Ham · Mincheol Shin · Dae-Shik Kim 🔗 |
|
-
|
CaloLatent: Score-based Generative Modelling in the Latent Space for Calorimeter Shower Generation
(
Poster
)
>
|
Thandikire Madula · Vinicius Mikuni 🔗 |
|
-
|
Predicting Galaxy Interloper Fraction with GNNs
(
Poster
)
>
|
Elena Massara · Francisco Villaescusa · Will Percival 🔗 |
|
-
|
ML-Enhanced Generalized Langevin Equation for Transient Anomalous Diffusion in Polymer Dynamics ( Poster ) > link | Gian-Michele Cherchi · Alain Dequidt · Patrice Hauret · Arnaud Guillin · Vincent Barra · Nicolas Martzel 🔗 |
|
-
|
Ensemble models outperform single model uncertainties and predictions for operator-learning of hypersonic flows
(
Poster
)
>
|
Victor Leon · Noah Ford · Honest Mrema · Jeffrey Gilbert · Alexander New 🔗 |
|
-
|
A Multi-Grained Group Symmetric Framework for Learning Protein-Ligand Binding Dynamics
(
Poster
)
>
|
11 presentersShengchao Liu · weitao du · Yanjing Li · Nakul Rampal · Zhuoxinran Li · Vignesh Bhethanabotla · Omar Yaghi · Christian Borgs · Anima Anandkumar · Hongyu Guo · Jennifer Chayes |
|
-
|
Discovering Black Hole Mass Scaling Relations with Symbolic Regression
(
Poster
)
>
|
Zehao Jin · Benjamin Davis 🔗 |
|
-
|
Hydrogen Diffusion through Polymer using Deep Reinforcement Learning
(
Poster
)
>
|
Tian Sang · Ken-ichi Nomura · Aiichiro Nakano · Rajiv Kalia · Priya Vashishta 🔗 |
|
-
|
Nonlinear-manifold reduced order models with domain decomposition
(
Poster
)
>
|
Alejandro Diaz · Youngsoo Choi · Matthias Heinkenschloss 🔗 |
|
-
|
A Multimodal Dataset and Benchmark for Radio Galaxy and Infrared Host Detection
(
Poster
)
>
|
Nikhel Gupta 🔗 |
|
-
|
PINNs-TF2: Fast and User-Friendly Physics-Informed Neural Networks in TensorFlow V2 ( Poster ) > link | Reza Akbarian Bafghi · Maziar Raissi 🔗 |
|
-
|
Extending Explainable Boosting Machines to Scientific Image Data
(
Poster
)
>
|
Daniel Schug · Sai Yerramreddy · Rich Caruana · Craig Greenberg · Justyna Zwolak 🔗 |
|
-
|
Fast Detection of Phase Transitions with Multi-Task Learning-by-Confusion
(
Poster
)
>
|
Julian Arnold · Frank Schäfer · Niels Lörch 🔗 |
|
-
|
A Data-Driven, Non-Linear, Parameterized Reduced Order Model of Metal 3D Printing
(
Poster
)
>
|
Aaron Brown · Eric Chin · Youngsoo Choi · Saad Khairallah · Joseph McKeown 🔗 |
|
-
|
Evaluating Physically Motivated Loss Functions for Photometric Redshift Estimation
(
Poster
)
>
|
Andrew Engel · Jan Strube 🔗 |
|
-
|
Variational quantum dynamics of two-dimensional rotor models
(
Poster
)
>
|
Matija Medvidović · Dries Sels 🔗 |
|
-
|
Pre-training strategy using real particle collision data for event classification in collider physics
(
Poster
)
>
|
Tomoe Kishimoto · Masahiro Morinaga · Masahiko Saito · Junichi Tanaka 🔗 |
|
-
|
Zephyr : Stitching Heterogeneous Training Data with Normalizing Flow for Photometric Redshift Inference
(
Poster
)
>
|
Zechang Sun · Joshua Speagle · Song Huang · Yuan-Sen Ting · Zheng Cai 🔗 |
|
-
|
Data-Driven Autoencoder Numerical Solver with Uncertainty Quantification for Fast Physical Simulations
(
Poster
)
>
|
Christophe Bonneville · Youngsoo Choi · Debojyoti Ghosh · Jon Belof 🔗 |
|
-
|
Uncovering Conformal Towers Using Deep Learning
(
Poster
)
>
|
Lior Oppenheim · Zohar Ringel · Snir Gazit · Maciej Koch-Janusz 🔗 |
|
-
|
Incremental learning for physics-informed neural networks
(
Poster
)
>
|
Aleksandr Dekhovich · Marcel Sluiter · David M.J. Tax · Miguel Bessa 🔗 |
|
-
|
GAMMA: Galactic Attributes of Mass, Metallicity, and Age Dataset ( Poster ) > link | Tobias Buck · Ufuk Çakır 🔗 |
|
-
|
Differential optimisation for task- and constraint-aware design of particle detectors
(
Poster
)
>
|
14 presentersGiles Strong · Maxime Lagrange · Aitor Orio Alonso · Anna Bordignon · Florian Bury · tommaso dorigo · Andrea Giammanco · Mariam Safieldin · Jan Kieseler · Max Lamparth · Pablo Martinez · Federico Nardi · Pietro Vischia · Haitham Zaraket |
|
-
|
Neural ODEs as a discovery tool to characterize the structure of the hot galactic wind of M82
(
Poster
)
>
|
Dustin Nguyen · Yuan-Sen Ting · Todd Thompson · Sebastian Lopez · Laura Lopez 🔗 |
|
-
|
Speeding up astrochemical reaction networks with autoencoders and neural ODEs
(
Poster
)
>
|
Tobias Buck · Immanuel Felix Sulzer 🔗 |
|
-
|
GalacticFlow: Learning a Generalized Representation of Galaxies with Normalizing Flows
(
Poster
)
>
|
Tobias Buck · Luca Wolf 🔗 |
|
-
|
PACuna: Automated Fine-Tuning of Language Models for Particle Accelerators
(
Poster
)
>
|
Antonin Sulc · Raimund Kammering · Annika Eichler · Tim Wilksen 🔗 |
|
-
|
Graph-Theoretical Approaches for AI-Driven Discovery in Quantum Optics
(
Poster
)
>
|
Xuemei Gu · Carlos Ruiz-Gonzalez · Sören Arlt · Tareq Jaouni · Jan Petermann · Sharareh Sayyad · Ebrahim Karimi · Nora Tischler · Mario Krenn 🔗 |
|
-
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Direct Amortized Likelihood Ratio Estimation
(
Poster
)
>
|
Adam Cobb · Brian Matejek · Daniel Elenius · Anirban Roy · Susmit Jha 🔗 |
|
-
|
Physics-informed neural networks with unknown measurement noise
(
Poster
)
>
|
Philipp Pilar · Niklas Wahlström 🔗 |
|
-
|
Universal Semantic-less Texture Boundary Detection for Microscopy (and Metallography)
(
Poster
)
>
|
Matan Rusanovsky · Ofer Beeri · Shai Avidan · Gal Oren 🔗 |
|
-
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Information bottleneck learns dominant transfer operator eigenfunctions in dynamical systems
(
Poster
)
>
|
Matthew S. Schmitt · Maciej Koch-Janusz · Michel Fruchart · Daniel Seara · Vincenzo Vitelli 🔗 |
|
-
|
Causa prima: cosmology meets causal discovery for the first time
(
Poster
)
>
|
Mario Pasquato · Zehao Jin · Pablo Lemos · Benjamin Davis · Andrea Macciò 🔗 |
|
-
|
Unraveling the Mysteries of Galaxy Clusters: Recurrent Inference Deconvolution of X-ray Spectra
(
Poster
)
>
|
Carter Rhea · Julie Hlavacek-Larrondo · Ralph Kraft · Akos Bogdan · Laurence Perreault-Levasseur · Alexandre Adam · John Zuhone 🔗 |
|
-
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Scalable physics-guided data-driven component model reduction for Stokes flow
(
Poster
)
>
|
Kevin Chung · Youngsoo Choi · Pratanu Roy · Thomas Moore · Thomas Roy · Tiras Y. Lin · Sarah Baker 🔗 |
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-
|
Improving dispersive readout of a superconducting qubit by machine learning on path signature
(
Poster
)
>
|
Shuxiang Cao · Zhen Shao · Jian-Qing Zheng · Mustafa Bakr · Peter Leek · Terry Lyons 🔗 |
|
-
|
Optimizing Likelihood-free Inference using Self-supervised Neural Symmetry Embeddings
(
Poster
)
>
|
Deep Chatterjee · Philip Harris · Maanas Goel · Malina Desai · Michael Coughlin · Erik Katsavounidis 🔗 |
|
-
|
Removing Dust from CMB Observations with Diffusion Models
(
Poster
)
>
|
David Heurtel-Depeiges · Blakesly Burkhart · Ruben Ohana · Bruno Régaldo-Saint Blancard 🔗 |
|
-
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$\rho$-Diffusion: A diffusion-based density estimation framework for computational physics
(
Poster
)
>
|
Maxwell Xu Cai · Kin Long Kelvin Lee 🔗 |
|
-
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Transformers for Scattering Amplitudes
(
Poster
)
>
|
Garrett Merz · Francois Charton · Tianji Cai · Kyle Cranmer · Lance Dixon · Niklas Nolte · Matthias Wilhelm 🔗 |
|
-
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NeuralHMC: Accelerated Hamiltonian Monte Carlo with a Neural Network Surrogate Likelihood
(
Poster
)
>
|
Linnea Wolniewicz · Peter Sadowski · Claudio Corti 🔗 |
|
-
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Discovering Galaxy Features via Dataset Distillation
(
Poster
)
>
|
Haowen Guan · Xuan Zhao · Zishi Wang · Zhiyang Li · Julia Kempe 🔗 |
|
-
|
Modeling Coupled 1D PDEs of Cardiovascular Flow with Spatial Neural ODEs
(
Poster
)
>
|
Hunor Csala · Arvind Mohan · Daniel Livescu · Amirhossein Arzani 🔗 |
|
-
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Generating Multiphase Fluid Configurations in Fractures using Diffusion Models
(
Poster
)
>
|
Jaehong Chung · Agnese Marcato · Eric Guiltinan · Tapan Mukerji · Yen Ting Lin · Javier E. Santos 🔗 |
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Redefining Super-Resolution:Fine-mesh PDE predictions without classical simulations
(
Poster
)
>
|
Rajat Sarkar · Ritam Majumdar · Vishal Jadhav · Sagar Srinivas Sakhinana · Venkataramana Runkana 🔗 |
|
-
|
Discovering Quantum Error Correcting Codes with Deep Reinforcement Learning
(
Poster
)
>
|
Jan Olle · Remmy Zen · Matteo Puviani · Florian Marquardt 🔗 |
|
-
|
Discovering Quantum Circuits for Logical State Preparation with Deep Reinforcement Learning
(
Poster
)
>
|
Remmy Zen · Jan Olle · Matteo Puviani · Florian Marquardt 🔗 |
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|
Differentiable Simulation of a Liquid Argon TPC for High-Dimensional Calibration
(
Poster
)
>
|
Pierre Granger 🔗 |
|
-
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Learning Hard Distributions with Quantum-enhanced Variational Autoencoders
(
Poster
)
>
|
Anantha Rao · Dhiraj Madan · Anupama Ray · Dhinakaran Vinayagamurthy · M S Santhanam 🔗 |
|
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Revealing the Mechanism of Large-scale Gradient Systems Using a Neural Reduced Potential
(
Poster
)
>
|
Shunya Tsuji · Ryo Murakami · Hayaru Shouno · Yoh-ichi Mototake 🔗 |
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-
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Physical Symbolic Optimization ( Poster ) > link | Wassim Tenachi · Rodrigo Ibata · Foivos Diakogiannis 🔗 |
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Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model
(
Poster
)
>
|
François Rozet · Gilles Louppe 🔗 |
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|
Physics-Informed Tensor Basis Neural Network for Turbulence Closure Modeling
(
Poster
)
>
|
Leon Riccius · Atul Agrawal · Phaedon S Koutsourelakis 🔗 |
|
-
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Relating Generalization in Deep Neural Networks to Sensitivity of Discrete Dynamical Systems
(
Poster
)
>
|
Jan Disselhoff · Michael Wand 🔗 |
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Orbital-Free Density Functional Theory with Continuous Normalizing Flows
(
Poster
)
>
|
Rodrigo Vargas-Hernandez · Ricky T. Q. Chen · Alexandre de Camargo 🔗 |
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-
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DeepTreeGANv2: Iterative Pooling of Point Clouds
(
Poster
)
>
|
Moritz A.W. Scham · Dirk Krücker · Kerstin Borras 🔗 |
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Robust Ocean Subgrid-Scale Parameterizations Using Fourier Neural Operators
(
Poster
)
>
|
Victor Mangeleer · Gilles Louppe 🔗 |
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3D Localization of Microparticles from Holographic Images using Neural Networks
(
Poster
)
>
|
Ayush Paliwal · Oliver Schlenczek · Birte Thiede · Gholamhossein Bagheri · Alexander Ecker 🔗 |
|
-
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Locating Hidden Exoplanets Using Machine Learning
(
Poster
)
>
|
Jason Terry · Sergei Gleyzer 🔗 |
|
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Learning Optical Map in Liquid Xenon Detector with Poisson Likelihood Loss
(
Poster
)
>
|
Shixiao Liang · Christopher Tunnell 🔗 |
|
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AstroYOLO: Learning Astronomy Multi-Tasks in a Single Unified Real-Time Framework
(
Poster
)
>
|
Nodirkhuja Khujaev · Roman Tsoy · Seungryul Baek 🔗 |
|
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Coarse graining systems on inhomogeneous graphs using contrastive learning
(
Poster
)
>
|
Doruk Efe Gökmen · Maciej Koch-Janusz · Zohar Ringel · Sebastian Huber · Felix Flicker · Sounak Biswas 🔗 |
|
-
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Understanding Pathologies of Deep Heteroskedastic Regression
(
Poster
)
>
|
Eliot Wong-Toi · Alex Boyd · Vincent Fortuin · Stephan Mandt 🔗 |
|
-
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Advancing Generative Modelling of Calorimeter Showers on Three Frontiers
(
Poster
)
>
|
12 presentersErik Buhmann · Sascha Diefenbacher · Engin Eren · Frank Gaede · Gregor Kasieczka · William Korcari · Anatolii Korol · Claudius Krause · Katja Krueger · Peter McKeown · Imahn Shekhzadeh · David Shih |
|
-
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Multi-fidelity Constrained Optimization for Stochastic Black Box Simulators
(
Poster
)
>
|
Kislaya Ravi · Atul Agrawal · Phaedon S Koutsourelakis · Hans-Joachim Bungartz 🔗 |
|
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Activation Functions in Non-Negative Neural Networks
(
Poster
)
>
|
Marlon Becker · Dominik Drees · Frank Brückerhoff-Plückelmann · Carsten Schuck · Wolfram Pernice · Benjamin Risse 🔗 |
|
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Tree-Based Algorithms for Weakly Supervised Anomaly Detection
(
Poster
)
>
|
Thorben Finke · Marie Hein · Gregor Kasieczka · Michael Krämer · Alexander Mück · Parada Prangchaikul · Tobias Quadfasel · David Shih · Manuel Sommerhalder 🔗 |
|
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HIDM: Emulating Large Scale HI Maps using Score-based Diffusion Models
(
Poster
)
>
|
Sultan Hassan · Sambatra Andrianomena 🔗 |
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Probabilistic-Machine-Learning-based Turbulence Model Learning with a Differentiable Solver
(
Poster
)
>
|
Atul Agrawal · Phaedon S Koutsourelakis 🔗 |
|
-
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AI ensemble for signal detection of higher order gravitational wave modes of quasi-circular, spinning, non-precessing binary black hole mergers
(
Poster
)
>
|
Minyang Tian · Eliu Huerta 🔗 |
|
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Latent space representations of cosmological fields
(
Poster
)
>
|
Sambatra Andrianomena · Sultan Hassan 🔗 |
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Enhancing Data-Assimilation in CFD using Graph Neural Networks
(
Poster
)
>
|
Michele Quattromini · Michele Alessandro Bucci · Stefania Cherubini · Onofrio Semeraro 🔗 |
|
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Gamma Ray AGNs: Estimating Redshifts and Blazar Classification using traditional Neural Networks with smart initialization and self-supervised learning
(
Poster
)
>
|
Sarvesh Gharat · Gopal Bhatta · ABHIMANYU BORTHAKUR 🔗 |
|
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Enhancing the local expressivity of geometric graph neural networks
(
Poster
)
>
|
Sam Walton Norwood · Lars L Schaaf · Ilyes Batatia · Arghya Bhowmik · Gabor Csanyi 🔗 |
|
-
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Domain Adaptation for Measurements of Strong Gravitational Lenses
(
Poster
)
>
|
Paxson Swierc · Yifan Zhao · Aleksandra Ciprijanovic · Brian Nord 🔗 |
|
-
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QDC: Quantum Diffusion Convolution Kernels on Graphs
(
Poster
)
>
|
Thomas Markovich 🔗 |
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Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation
(
Poster
)
>
|
Ryan Liu · Abhijith Gandrakota · Jennifer Ngadiuba · jean-roch vlimant · Maria Spiropulu 🔗 |
|
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Fast Particle-based Anomaly Detection Algorithm with Variational Autoencoder
(
Poster
)
>
|
Ryan Liu · Abhijith Gandrakota · Jennifer Ngadiuba · jean-roch vlimant · Maria Spiropulu 🔗 |
|
-
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Preparing Spectral Data for Machine Learning: A Study of Geological Classification from Aerial Surveys
(
Poster
)
>
|
Jun Woo Chung · Alex Sim · Brian Quiter · Yuxin Wu · Weijie Zhao · Kesheng Wu 🔗 |
|
-
|
Loss-driven sampling within hard-to-learn areas for simulation-based neural network training ( Poster ) > link | Sofya Dymchenko · Bruno Raffin 🔗 |
|
-
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Long Time Series Data Release from Broadband Axion Dark Matter Experiment
(
Poster
)
>
|
Jessica Fry · Aobo Li 🔗 |
|
-
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Physics - Informed Machine Learning for Reduced Space Chemical Kinetics
(
Poster
)
>
|
Anuj Kumar · Tarek Echekki 🔗 |
|
-
|
Smartpixels: Towards on-sensor inference of charged particle track parameters and uncertainties
(
Poster
)
>
|
22 presentersLindsey Gray · Jennet Dickinson · Rachel Kovach-Fuentes · Morris Swartz · Giuseppe Di Guglielmo · Alice Bean · Douglas Berry · Manuel Blanco Valentin · Karri DiPetrillo · Farah Fahim · Jim Hirschauer · Shruti Kulkarni · Ron Lipton · Petar Maksimovic · Corrinne Mills · Mark Neubauer · Benjamin Parpillon · Gauri Pradhan · Chinar Syal · Nhan Tran · Jieun Yoo · Aaron Young |
|
-
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On Representations of Mean-Field Variational Inference
(
Poster
)
>
|
Soumyadip Ghosh · Yingdong Lu · Tomasz Nowicki · Edith Zhang 🔗 |
|
-
|
Active learning meets fractal decision boundaries: a cautionary tale from the Sitnikov three body problem
(
Poster
)
>
|
Nicolas Payot · Mario Pasquato · Alessandro Alberto Trani · Yashar Hezaveh · Laurence Perreault-Levasseur 🔗 |
|
-
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A deep learning framework for jointly extracting spectra and source-count distributions of count maps
(
Poster
)
>
|
Florian Wolf · Florian List · Nicholas Rodd · Oliver Hahn 🔗 |
|
-
|
Machine learning-based compression of quantum many body physics: PCA and autoencoder representation of the vertex function
(
Poster
)
>
|
Jiawei Zang · Matija Medvidović · Dominik Kiese · Domenico Di Sante · Anirvan Sengupta · Andy Millis 🔗 |
|
-
|
Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets
(
Poster
)
>
|
Andrea Roncoli · Aleksandra Ciprijanovic · M Voetberg · Francisco Villaescusa · Brian Nord 🔗 |
|
-
|
Multibasis Encodings in Recurrent Neural Network Wave Functions for Variational Optimization
(
Poster
)
>
|
Wirawat Kokaew 🔗 |
|
-
|
Simulation Based Inference of BNS Kilonova Properties: A Case Study with AT2017gfo
(
Poster
)
>
|
Phelipe Darc · Clecio Bom · Bernardo Fraga · Charles D. Kilpatrick 🔗 |
|
-
|
Physics-aware Modeling of an Accelerated Particle Cloud
(
Poster
)
>
|
Emmanuel Goutierre · Hayg Guler · Christelle Bruni · Johanne Cohen · Michele Sebag 🔗 |
|
-
|
Optimized Dry Cooling for Solar Power Plants
(
Poster
)
>
|
Hansley Narasiah · Ouail Kitouni · Andrea Scorsoglio · Bernd Sturdza · Shawn Hatcher · Dolores Garcia · Matt Kusner 🔗 |
|
-
|
A Physics-Constrained NeuralODE Approach for Robust Learning of Stiff Chemical Kinetics
(
Poster
)
>
|
Tadbhagya Kumar · Anuj Kumar · Pinaki Pal 🔗 |
|
-
|
Trick or treat? Evaluating stability strategies in graph network-based simulators
(
Poster
)
>
|
Omer Rochman Sharabi · Gilles Louppe 🔗 |
|
-
|
Super-Resolution Emulation of Large Cosmological Fields with a 3D Conditional Diffusion Model
(
Poster
)
>
|
Adam Rouhiainen · Michael Gira · Gary Shiu · Kangwook Lee · Moritz Münchmeyer 🔗 |
|
-
|
Equivariant Networks for Robust Galaxy Morphology Classification
(
Poster
)
>
|
Sneh Pandya · Purvik Patel · Franc O · Jonathan Blazek 🔗 |
|
-
|
Reduced-order modeling for parameterized PDEs via implicit neural representations
(
Poster
)
>
|
Tianshu Wen · Kookjin Lee · Youngsoo Choi 🔗 |
|
-
|
Simulation-Based Inference for Detecting Blending in Spectra
(
Poster
)
>
|
Declan McNamara · Jeffrey Regier 🔗 |
|
-
|
JETLOV: Enhancing Jet Tree Tagging through Neural Network Learning of Optimal LundNet Variables
(
Poster
)
>
|
Giorgio Cerro 🔗 |
|
-
|
Hierarchical Cross-entropy Loss for Classification of Astrophysical Transients
(
Poster
)
>
|
V Villar 🔗 |
|
-
|
Surrogate Model Training Data for FIDVR-related Voltage Control in Large-scale Power Grids
(
Poster
)
>
|
Tianzhixi Yin · Renke Huang · Ramij Raja Hossain · Qiuhua Huang · Jie Tan · Wenhao Yu 🔗 |
|
-
|
Differentiable, End-to-End Forward Modeling for 21 cm Cosmology: Robust Systematics Error Budgeting and More
(
Poster
)
>
|
Nicholas Kern 🔗 |
|
-
|
Investigating the Ability of PINNs To Solve Burgers’ PDE Near Finite-Time BlowUp
(
Poster
)
>
|
Dibyakanti Kumar · Anirbit Mukherjee 🔗 |
|
-
|
Detection and Segmentation of Ice Blocks in Europa's Chaos Terrain Using Mask R-CNN ( Poster ) > link | Marina Dunn · Conor Nixon · Alyssa Mills · Ahmed Awadallah · Ethan Duncan · John Santerre · Douglas Trent · Andrew Larsen 🔗 |
|
-
|
Neural Networks vs. Whittaker Smoothing: Advanced Techniques for Scattering Signal Removal in 3D Fluorescence spectra
(
Poster
)
>
|
Aleksandr Zakuskin · Ivan Krylov · Timur Labutin 🔗 |
|
-
|
Benchmarking of Fast and Interpretable UF Machine Learning Potentials
(
Poster
)
>
|
Pawan Prakash 🔗 |
|
-
|
A Physics-Informed Variational Autoencoder for Rapid Galaxy Inference and Anomaly Detection
(
Poster
)
>
|
Alex Gagliano · Ashley Villar 🔗 |
|
-
|
Pythia: A prototype artificial agent for designing optimal gravitational-wave follow-up campaigns
(
Poster
)
>
|
Niharika Sravan · Matthew Graham · Michael Coughlin · Shreya Anand · Tomas Ahumada 🔗 |
|
-
|
Probabilistic Reconstruction of Dark Matter fields from galaxies using diffusion models
(
Poster
)
>
|
Carolina Cuesta · Yueying Ni · Core Francisco Park · Nayantara Mudur · Victoria Ono 🔗 |
|
-
|
Predicting the Age of Astronomical Transients from Real-Time Multivariate Time Series
(
Poster
)
>
|
Daniel Muthukrishna 🔗 |
|
-
|
Multiscale Feature Attribution for Outliers
(
Poster
)
>
|
Jeff Shen · Peter Melchior 🔗 |
|
-
|
Learning Reionization History from Quasars with Simulation-Based Inference
(
Poster
)
>
|
Huanqing Chen · Joshua Speagle · Keir Rogers 🔗 |
|
-
|
Interpretable Joint Event-Particle Reconstruction at NOvA with Sparse CNNs and Transformers
(
Poster
)
>
|
Alexander Shmakov · Alejandro Yankelevich · Jianming Bian · Pierre Baldi 🔗 |
|
-
|
SimSIMS: Simulation-based Supernova Ia Model Selection with thousands of latent variables
(
Poster
)
>
|
Konstantin Karchev · Roberto Trotta · Christoph Weniger 🔗 |
|
-
|
Accelerating Kinetic Simulations of Electrostatic Plasmas with Reduced-Order Modeling
(
Poster
)
>
|
Ping-Hsuan Tsai · Kevin Chung · Debojyoti Ghosh · John Loffeld · Youngsoo Choi · Jon Belof 🔗 |
|
-
|
Sequential Monte Carlo for Detecting and Deblending Objects in Astronomical Images
(
Poster
)
>
|
Tim White · Jeffrey Regier 🔗 |
|
-
|
DeepSurveySim: Simulation Software and Benchmark Challenges for Astronomical Observation Scheduling
(
Poster
)
>
|
M Voetberg · Brian Nord 🔗 |
|
-
|
LoDIP: Low-dose phase retrieval with deep image prior
(
Poster
)
>
|
Raunak Manekar · Elisa Negrini · Minh Pham · Daniel Jacobs · Jaideep Srivastava · Stanley Osher · Jianwei Miao 🔗 |
|
-
|
Bayesian multi-band fitting of alerts for kilonovae detection
(
Poster
)
>
|
Biswajit Biswas 🔗 |
|
-
|
Forward Gradients for Data-Driven CFD Wall Models
(
Poster
)
>
|
Jan Hueckelheim · Tadbhagya Kumar · Krishnan Raghavan · Pinaki Pal 🔗 |
|
-
|
Learning an Effective Evolution Equation for Particle-Mesh Simulations Across Cosmologies
(
Poster
)
>
|
Nicolas Payot · Pablo Lemos · Laurence Perreault-Levasseur · Carolina Cuesta · Chirag Modi · Yashar Hezaveh 🔗 |
|
-
|
Active Learning for Discovering Complex Phase Diagrams with Gaussian Processes
(
Poster
)
>
|
Max Zhu · Jian Yao · Marcus Mynatt · Hubert Pugzlys · Shuyi Li · Qingyuan Zhao · Chunjing Jia 🔗 |
|
-
|
RACER: Rational Artificial Intelligence Car-following-model Enhanced by Reality
(
Poster
)
>
|
Tianyi Li · Raphael Stern 🔗 |
|
-
|
Learned integration contour deformation for signal-to-noise improvement in Monte Carlo calculations
(
Poster
)
>
|
William Detmold · Gurtej Kanwar · Yin Lin · Phiala Shanahan · Michael Wagman 🔗 |
|
-
|
The search for the lost attractor
(
Poster
)
>
|
11 presentersMario Pasquato · Syphax Haddad · Pierfrancesco Di Cintio · Alexandre Adam · Noé Dia · Mircea Petrache · Ugo Niccolò Di Carlo · Alessandro Alberto Trani · Laurence Perreault-Levasseur · Yashar Hezaveh · Pablo Lemos |
|
-
|
Field Emulation and Parameter Inference with Diffusion Models
(
Poster
)
>
|
Nayantara Mudur · Carolina Cuesta · Douglas P. Finkbeiner 🔗 |
|
-
|
Symbolic Machine Learning for High Energy Physics Calculations
(
Poster
)
>
|
Abdulhakim Alnuqaydan · Sergei Gleyzer · Harrison Prosper · Eric Reinhardt · Francois Charton · Neeraj Anand 🔗 |
|
-
|
Autoencoding Labeled Interpolator, Inferring Parameters From Image And Image From Parameters
(
Poster
)
>
|
Ali SaraerToosi · Avery Broderick 🔗 |
|
-
|
Leveraging Deep Learning for Physical Model Bias of Global Air Quality Estimates
(
Poster
)
>
|
Kelsey Doerksen · Yarin Gal · Freddie Kalaitzis · Yuliya Marchetti · Steven Lu · James Montgomery · Kazuyuki Miyazaki · Kevin Bowman 🔗 |
|
-
|
Towards data-driven models of hadronization
(
Poster
)
>
|
Christian Bierlich · Philip Ilten · Tony Menzo · Stephen Mrenna · Manuel Szewc · Michael K. Wilkinson · Ahmed Youssef · Jure Zupan 🔗 |
|
-
|
From Plateaus to Progress: Unveiling Training Dynamics of PINNs
(
Poster
)
>
|
Daniel Lengyel · Panos Parpas · Rahil Pandya 🔗 |
|
-
|
Equivariant Neural Networks for Signatures of Dark Matter Morphology in Strong Lensing Data
(
Poster
)
>
|
Geo Jolly Cheeramvelil · Michael Toomey · Sergei Gleyzer 🔗 |
|
-
|
Echoes in the Noise: Posterior Samples of Faint Galaxy Surface Brightness Profiles with Score-Based Likelihoods and Priors
(
Poster
)
>
|
Alexandre Adam · Connor Stone · Connor Bottrell · Ronan Legin · Laurence Perreault-Levasseur · Yashar Hezaveh 🔗 |
|
-
|
Deep Learning Segmentation of Spiral Arms and Bars
(
Poster
)
>
|
Mike Walmsley · Ashley Spindler 🔗 |
|
-
|
Accelerating Flow Simulations using Online Dynamic Mode Decomposition
(
Poster
)
>
|
Seung Won Suh · Kevin Chung · Timo Bremer · Youngsoo Choi 🔗 |
|
-
|
Sparse 3D Images: Point Cloud or Image methods?
(
Poster
)
>
|
Fernando Torales Acosta · Vinicius Mikuni · Benjamin Nachman · Miguel Arratia · Bishnu Karki · Ryan Milton · Piyush Karande · Aaron Angerami 🔗 |
|
-
|
Classification under Prior Probability Shift in Simulator-Based Inference: Application to Atmospheric Cosmic-Ray Showers
(
Poster
)
>
|
Alexander Shen · Ann Lee · Luca Masserano · tommaso dorigo · Michele Doro · Rafael Izbicki 🔗 |
|
-
|
Rare Galaxy Classes Identified In Foundation Model Representations
(
Poster
)
>
|
Mike Walmsley · Anna Scaife 🔗 |
|
-
|
Understanding and Visualizing Droplet Distributions in Simulations of Shallow Clouds
(
Poster
)
>
|
Justus C. Will · Andrea Jenney · Kara Lamb · Mike Pritchard · Colleen Kaul · Po-Lun Ma · Jacob Shpund · Kyle Pressel · Marcus van Lier-Walqui · Stephan Mandt 🔗 |
|
-
|
Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e
(
Poster
)
>
|
23 presentersJerry Yao-Chieh Hu · Chenwei Xu · Aakaash Narayanan · Mattson Thieme · Vladimir Nagaslaev · Mark Austin · Jeremy Arnold · Jose Berlioz · Pierrick Hanlet · Aisha Ibrahim · Dennis Nicklaus · Jovan Mitrevski · Gauri Pradhan · Andrea Saewert · Kiyomi Seiya · Brian Schupbach · Randy Thurman-Keup · Nhan Tran · Rui Shi · Seda Ogrenci · Alexis Maya-Isabelle Shuping · Kyle Hazelwood · Han Liu |
|
-
|
Loss Functionals for Learning Likelihood Ratios
(
Poster
)
>
|
Shahzar Rizvi · Mariel Pettee · Benjamin Nachman 🔗 |
|
-
|
19 Parameters Is All You Need: Tiny Neural Networks for Particle Physics
(
Poster
)
>
|
Alexander Bogatskiy · Timothy Hoffman · Jan Offermann 🔗 |
|
-
|
CP-PINNs: Changepoints Detection in PDEs using Physics Informed Neural Networks with Total-Variation Penalty
(
Poster
)
>
|
Zhikang Dong · Pawel Polak 🔗 |
|
-
|
Self-Driving Telescopes: Autonomous Scheduling of Astronomical Observation Campaigns with Offline Reinforcement Learning
(
Poster
)
>
|
Franco Terranova · M Voetberg · Brian Nord · Amanda Pagul 🔗 |
|
-
|
High-dimensional and Permutation Invariant Anomaly Detection with Diffusion Generative Models
(
Poster
)
>
|
Vinicius Mikuni · Benjamin Nachman 🔗 |
|
-
|
Generative Diffusion Models for Lattice Field Theory
(
Poster
)
>
|
Lingxiao Wang · Gert Aarts · Kai Zhou 🔗 |
|
-
|
Reconstruction of Fields from Sparse Sensing: Differentiable Sensor Placement Enhances Generalization
(
Poster
)
>
|
Agnese Marcato · Daniel O'Malley · Hari Viswanathan · Eric Guiltinan · Javier E. Santos 🔗 |
|
-
|
Learning Dark Matter Representation from Strong Lensing Images through Self-Supervision
(
Poster
)
>
|
Yashwardhan Deshmukh · Kartik Sachdev · Michael Toomey · Sergei Gleyzer 🔗 |
|
-
|
Graph Neural Networks for Identifying Protein Reactive Compounds
(
Poster
)
>
|
Victor Hugo Cano Gil · Christopher Rowley 🔗 |
|
-
|
Towards out-of-distribution generalization: robust networks learn similar representations
(
Poster
)
>
|
Yash Gondhalekar · Sultan Hassan · Naomi Saphra · Sambatra Andrianomena 🔗 |
|
-
|
Towards an Astronomical Foundation Model for Stars
(
Poster
)
>
|
Henry Leung 🔗 |
|
-
|
Induced Generative Adversarial Particle Transformers
(
Poster
)
>
|
Anni Li · Venkat Krishnamohan · Raghav Kansal · Javier Duarte · Rounak Sen · Steven Tsan · Zhaoyu Zhang 🔗 |
|
-
|
Lensformer: A Physics-Informed Vision Transformer for Gravitational Lensing
(
Poster
)
>
|
Lucas José Velôso de Souza · Michael Toomey · Sergei Gleyzer 🔗 |
|
-
|
Self-supervised learning for searching jellyfish galaxies in the ocean of data from upcoming surveys
(
Poster
)
>
|
Yash Gondhalekar · Rafael de Souza · Ana Chies Santos · Carolina Queiroz 🔗 |
|
-
|
deep-REMAP: Parameterization of Stellar Spectra Using Regularized Multi-Task Learning
(
Poster
)
>
|
Sankalp Gilda 🔗 |
|
-
|
Bayesian Simulation-based Inference for Cosmological Initial Conditions
(
Poster
)
>
|
Noemi Anau Montel · Florian List · Christoph Weniger 🔗 |
|
-
|
Autoregressive Transformers for Disruption Prediction in Nuclear Fusion Plasmas
(
Poster
)
>
|
Lucas Spangher · William Arnold · Alexander Spangher · Andrew Maris · Cristina Rea 🔗 |
|
-
|
CaloFFJORD: High Fidelity Calorimeter Simulation Using Continuous Normalizing Flows
(
Poster
)
>
|
Chirag Furia · Vinicius Mikuni 🔗 |
|
-
|
Machine learning-assisted nanoscale photoelectrical sensing
(
Poster
)
>
|
Ziyan Zhu · Zhurun (Judy) Ji · Houssam Yassin · Zhi-Xun Shen · Thomas Devereaux 🔗 |
|
-
|
Emulating deviations from Einstein's General Relativity using conditional GANs
(
Poster
)
>
|
Yash Gondhalekar · Sownak Bose 🔗 |
|
-
|
Operator SVD with Neural Networks via Nested Low-Rank Approximation ( Poster ) > link | Jongha (Jon) Ryu · Xiangxiang Xu · Hasan Sabri Melihcan Erol · Yuheng Bu · Lizhong Zheng · Gregory Wornell 🔗 |
|
-
|
Gradient weighted physics-informed neural networks for capturing shocks in porous media flows
(
Poster
)
>
|
Somiya Kapoor · Abhishek Chandra · Taniya Kapoor · Mitrofan Curti 🔗 |
|
-
|
Physics-Informed Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems using Liquid Time-Constant Networks ( Poster ) > link | Favour Nerrise · Andrew Sosanya · Patrick Neary 🔗 |
|
-
|
The DL Advocate: Playing the devil’s advocate with hidden systematic uncertainties
(
Poster
)
>
|
Andrey Ustyuzhanin · Andrey Golutvin · Aleksandr Iniukhin · Patrick Owen · Andrea Mauri · Nicola Serra 🔗 |
|
-
|
MCMC to address model misspecification in Deep Learning classification of Radio Galaxies
(
Poster
)
>
|
Devina Mohan · Anna Scaife 🔗 |
|
-
|
Application of Zone Method based Physics-Informed Neural Networks in Reheating Furnaces
(
Poster
)
>
|
Ujjal Dutta · Aldo Lipani · Chuan Wang · Yukun Hu 🔗 |
|
-
|
LEO Satellite Orbit Prediction with Physics Informed Machine Learning
(
Poster
)
>
|
Francesco Alesiani · Makoto Takamoto · Toshio Kamiya · Daisuke Etou 🔗 |
|
-
|
Physically Accurate Fast Nanophotonic Simulations with Physics Informed Model and Training
(
Poster
)
>
|
Ahmet Onur Dasdemir · Can Dimici · Aykut Erdem · Emir Salih Magden 🔗 |
|
-
|
Bayesian Imaging for Radio Interferometry with Score-Based Priors
(
Poster
)
>
|
Noé Dia · M. J. Yantovski-Barth · Alexandre Adam · Micah Bowles · Pablo Lemos · Laurence Perreault-Levasseur · Yashar Hezaveh · Anna Scaife 🔗 |
|
-
|
Virtual EVE: a Deep Learning Model for Solar Irradiance Prediction
(
Poster
)
>
|
Manuel Indaco · Daniel Gass · William Fawcett · Richard Galvez · Paul Wright · Andres Munoz-Jaramillo 🔗 |
|
-
|
High-Cadence Thermospheric Density Estimation enabled by Machine Learning on Solar Imagery
(
Poster
)
>
|
Shreshth Malik · James Edward Joseph Walsh · Giacomo Acciarini · Thomas Berger · Atilim Gunes Baydin 🔗 |
|
-
|
Combining astrophysical datasets with CRUMB
(
Poster
)
>
|
Fiona Porter 🔗 |
|
-
|
Ultra Fast Transformers on FPGAs for Particle Physics Experiments
(
Poster
)
>
|
Zhixing Jiang · Ziang Yin · Elham E Khoda · Vladimir Loncar · Ekaterina Govorkova · Eric Moreno · Philip Harris · Scott Hauck · Shih-chieh Hsu 🔗 |
|
-
|
Unleashing the Potential of Fractional Calculus in Graph Neural Networks
(
Poster
)
>
|
Qiyu Kang · Kai Zhao · Qinxu Ding · Feng Ji · Xuhao Li · WENFEI LIANG · Yang Song · Wee Peng Tay 🔗 |
|
-
|
Approximately-invariant neural networks for quantum many-body physics
(
Poster
)
>
|
Dominik Kufel · Jack Kemp · Norman Yao 🔗 |
|
-
|
Pseudotime Diffusion
(
Poster
)
>
|
Jacob Moss · Jeremy England · Pietro Lió 🔗 |
|
-
|
Reinforcement Learning for Ising Model
(
Poster
)
>
|
Yichen Lu · Xiao-Yang Liu 🔗 |
|
-
|
Reconstructing Free Energy Using Bayesian Thermodynamic Integration
(
Poster
)
>
|
Alexander Lobashev · Mikhail Tamm 🔗 |
|
-
|
ELUQuant: Event-Level Uncertainty Quantification using Physics-Informed Bayesian Neural Networks with Flow approximated Posteriors - A DIS Study
(
Poster
)
>
|
Cristiano Fanelli · James Giroux 🔗 |