Workshop
AI for Science: Progress and Promises
Yi Ding · Yuanqi Du · Tianfan Fu · Hanchen Wang · Anima Anandkumar · Yoshua Bengio · Anthony Gitter · Carla Gomes · Aviv Regev · Max Welling · Marinka Zitnik
Room 388 - 390
Fri 2 Dec, 6 a.m. PST
Chat is not available.
Timezone: America/Los_Angeles
Schedule
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Fri 6:00 a.m. - 6:15 a.m.
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Opening Remark
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Opening Remark
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Fri 6:15 a.m. - 7:10 a.m.
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Invited Talk Prof. Weinan E
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Fri 7:10 a.m. - 8:05 a.m.
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Invited Talk Prof. Shuiwang Ji
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Fri 8:05 a.m. - 8:15 a.m.
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Break
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Fri 8:15 a.m. - 9:10 a.m.
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Invited Talk Dr. Maria Schuld
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Fri 9:10 a.m. - 10:05 a.m.
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Invited Talk Prof. David Baker
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Fri 10:05 a.m. - 11:00 a.m.
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Poster Session I
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Poster
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Fri 11:00 a.m. - 11:10 a.m.
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Oral Presentation 1
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Oral
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Fri 11:10 a.m. - 11:20 a.m.
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Oral Presentation 2
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Fri 11:20 a.m. - 11:30 a.m.
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Oral Presentation 3
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Fri 11:30 a.m. - 11:40 a.m.
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Oral Presentation 4
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Fri 11:40 a.m. - 11:50 a.m.
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Oral Presentation 5
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Fri 11:55 a.m. - 12:55 p.m.
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Panel
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Fri 12:55 p.m. - 1:10 p.m.
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Break
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Fri 1:10 p.m. - 2:05 p.m.
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Invited Talk Prof. Jimeng Sun
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Fri 2:05 p.m. - 3:00 p.m.
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Invited Talk Prof. Tess Smidt
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Fri 3:00 p.m. - 3:10 p.m.
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Closing Remark
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Fri 3:10 p.m. - 4:00 p.m.
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Poster Session II
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Readability of Scientific Papers for English Learners in Various Fields of Science ( Poster ) > link | Yo Ehara 🔗 |
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Discovering ordinary differential equations that govern time-series ( Poster ) > link | Sören Becker · Michal Klein · Alexander Neitz · Giambattista Parascandolo · Niki Kilbertus 🔗 |
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Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks ( Poster ) > link | Ryien Hosseini · Filippo Simini · Austin Clyde · Arvind Ramanathan 🔗 |
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Structural Causal Model for Molecular Dynamics Simulation ( Oral ) > link | Qi Liu · Yuanqi Du · Fan Feng · Qiwei Ye · Jie Fu 🔗 |
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Pre-training via Denoising for Molecular Property Prediction ( Poster ) > link | Sheheryar Zaidi · Michael Schaarschmidt · James Martens · Hyunjik Kim · Yee Whye Teh · Alvaro Sanchez Gonzalez · Peter Battaglia · Razvan Pascanu · Jonathan Godwin 🔗 |
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Automated Protein Function Description for Novel Class Discovery ( Poster ) > link | Meet Barot · Vladimir Gligorijevic · Richard Bonneau · Kyunghyun Cho 🔗 |
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Structure-Inducing Pre-training ( Poster ) > link | TestMatt TestMcDermott · Brendan Yap · Peter Szolovits · Marinka Zitnik 🔗 |
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Physics-Embedded Neural Networks: Graph Neural PDE Solvers with Mixed Boundary Conditions ( Poster ) > link | Masanobu Horie · NAOTO MITSUME 🔗 |
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Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design ( Poster ) > link | Ilia Igashov · Hannes Stärk · Clément Vignac · Victor Garcia Satorras · Pascal Frossard · Max Welling · Michael Bronstein · Bruno Correia 🔗 |
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Publicly Available Privacy-preserving Benchmarks for Polygenic Prediction ( Poster ) > link | Menno Witteveen · Menno Witteveen 🔗 |
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Bi-channel Masked Graph Autoencoders for Spatially Resolved Single-cell Transcriptomics Data Imputation ( Poster ) > link | Hongzhi Wen · Wei Jin · Jiayuan Ding · Christopher Xu · Yuying Xie · Jiliang Tang 🔗 |
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Graph Neural Networks for Multimodal Single-Cell Data Integration ( Poster ) > link | Hongzhi Wen · Jiayuan Ding · Wei Jin · Yiqi Wang · Yuying Xie · Jiliang Tang 🔗 |
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A Pareto-optimal compositional energy-based model for sampling and optimization of protein sequences ( Poster ) > link |
12 presentersNataša Tagasovska · Nathan Frey · Andreas Loukas · Isidro Hotzel · Julien Lafrance-Vanasse · Ryan Kelly · Yan Wu · Arvind Rajpal · Richard Bonneau · Kyunghyun Cho · Stephen Ra · Vladimir Gligorijevic |
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Retrieval-based Controllable Molecule Generation ( Poster ) > link | Jack Wang · Weili Nie · Zhuoran Qiao · Chaowei Xiao · Richard Baraniuk · Anima Anandkumar 🔗 |
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Towards Neural Variational Monte Carlo That Scales Linearly with System Size ( Poster ) > link | Or Sharir · Garnet Chan · Anima Anandkumar 🔗 |
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Predicting Immune Escape with Pretrained Protein Language Model Embeddings ( Poster ) > link | Kyle Swanson · Howard Chang · James Zou 🔗 |
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Minimax Optimal Kernel Operator Learning via Multilevel Training ( Poster ) > link | Jikai Jin · Yiping Lu · Jose Blanchet · Lexing Ying 🔗 |
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Identifying Witnesses to Noise Transients in Ground-based Gravitational-wave Observations using Auxiliary Channels with Matrix and Tensor Factorization Techniques ( Poster ) > link | Rutuja Gurav · Vagelis Papalexakis · Gabriele Vajente · Jonathan Richardson · Barry Barish 🔗 |
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Data-driven Acceleration of Quantum Optimization and Machine Learning via Koopman Operator Learning ( Poster ) > link | Di Luo · Jiayu Shen · Rumen Dangovski · Marin Soljacic 🔗 |
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Knowledge-Guided Transfer Learning for Modeling Subsurface Phenomena Under Data Paucity ( Poster ) > link | Nikhil Muralidhar · NIcholas Lubbers · Mohamed Mehana · Naren Ramakrishnan · Anuj Karpatne 🔗 |
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Tabular deep learning when $d \gg n$ by using an auxiliary knowledge graph ( Poster ) > link | Camilo Ruiz · Hongyu Ren · Kexin Huang · Jure Leskovec 🔗 |
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Gauge Equivariant Neural Networks for 2+1D U(1) Gauge Theory Simulations in Hamiltonian Formulation ( Poster ) > link | Di Luo · Shunyue Yuan · James Stokes · Bryan Clark 🔗 |
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PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design ( Poster ) > link | Ji Won Park · Samuel Stanton · Saeed Saremi · Andrew Watkins · Stephen Ra · Vladimir Gligorijevic · Kyunghyun Cho · Richard Bonneau 🔗 |
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Resolving Computational Challenges in Accelerating Electronic Structure Calculations using Machine Learning ( Poster ) > link | James S Fox · J. Adam Stephens · Normand Modine · Laura Swiler · Sivasankaran Rajamanickam 🔗 |
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Conditioned Spatial Downscaling of Climate Variables ( Poster ) > link | Alex Hung · Evan Becker · Ted Zadouri · Aditya Grover 🔗 |
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Incorporating Higher Order Constraints for Training Surrogate Models to Solve Inverse Problems ( Poster ) > link | Jihui Jin · Nick Durofchalk · Richard Touret · Karim Sabra · Justin Romberg 🔗 |
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Incremental Fourier Neural Operator ( Poster ) > link | Jiawei Zhao · Robert Joseph George · Yifei Zhang · Zongyi Li · Anima Anandkumar 🔗 |
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Neural Unbalanced Optimal Transport via Cycle-Consistent Semi-Couplings ( Poster ) > link | Frederike Lübeck · Charlotte Bunne · Gabriele Gut · Jacobo Sarabia del Castillo · Lucas Pelkmans · David Alvarez-Melis 🔗 |
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Improving Classification and Data Imputation for Single-Cell Transcriptomics with Graph Neural Networks ( Poster ) > link | Han-Bo Li · Ramon Viñas Torné · Pietro Lió 🔗 |
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FALCON: Fourier Adaptive Learning and Control for Disturbance Rejection Under Extreme Turbulence ( Poster ) > link | Sahin Lale · Peter Renn · Kamyar Azizzadenesheli · Babak Hassibi · Morteza Gharib · Anima Anandkumar 🔗 |
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Critical Temperature Prediction of Superconductors Based on Machine Learning: A Short Review ( Poster ) > link | Juntao Jiang · Renjun Xu 🔗 |
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Toward Human-AI Co-creation to Accelerate Material Discovery ( Poster ) > link | Dmitry Zubarev · Carlos Raoni Mendes · Emilio Vital Brazil · Renato Cerqueira · Kristin Schmidt · Vinicius Segura · Juliana Ferreira · Daniel Sanders 🔗 |
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Robust task-specific adaption of models for drug-target interaction prediction ( Poster ) > link | Emma Svensson · Pieter-Jan Hoedt · Sepp Hochreiter · Günter Klambauer 🔗 |
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Surrogate modeling of stress fields in periodic polycrystalline microstructures using U-Net and Fourier neural operators ( Poster ) > link | Sarthak Kapoor · Jaber Mianroodi · Bob Svendsen · Mohammad Khorrami · Nima Siboni 🔗 |
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Deep Learning for Reference-Free Geolocation of Poplar Trees ( Poster ) > link | Cai John · Owen Queen · Scott Emrich · Wellington Muchero 🔗 |
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Solar Flare Forecasting with Data-driven Interpretable Model ( Poster ) > link | JiaMeng Lv · Peng Jia · 陈风 · 杨过 · Tie Liu 🔗 |
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So ManyFolds, So Little Time: Efficient Protein Structure Prediction with pLMs and MSAs ( Poster ) > link | Thomas D Barrett · Amelia Villegas-Morcillo · Louis Robinson · Benoit Gaujac · David Admète · Elia Saquand · Karim Beguir · Arthur Flajolet 🔗 |
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An "interpretable-by-design" neural network to decipher RNA splicing regulatory logic ( Poster ) > link | Susan Liao · Mukund Sudarshan · Oded Regev 🔗 |
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Physics-informed inference of animal movements from weather radar data ( Poster ) > link | Fiona Lippert · Patrick Forré 🔗 |
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SRSD: Rethinking Datasets of Symbolic Regression for Scientific Discovery ( Poster ) > link | Yoshitomo Matsubara · Naoya Chiba · Ryo Igarashi · Yoshitaka Ushiku 🔗 |
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Diffusion-based Molecule Generation with Informative Prior Bridges ( Poster ) > link | Chengyue Gong · Lemeng Wu · Xingchao Liu · Mao Ye · Qiang Liu 🔗 |
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Multiresolution Mesh Networks For Learning Dynamical Fluid Simulations ( Poster ) > link | Bach Nguyen · Truong Son Hy · Long Tran-Thanh · Risi Kondor 🔗 |
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Li-ion Battery Material phase prediction through Hierarchical Curriculum Learning ( Poster ) > link | Anika Tabassum · Nikhil Muralidhar · Ramakrishnan Kannan · Srikanth Allu 🔗 |
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Interpretable Geometric Deep Learning via Learnable Randomness Injection ( Poster ) > link | Siqi Miao · Yunan Luo · Mia Liu · Pan Li 🔗 |
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Fourier Continuation for Exact Derivative Computation in Physics-Informed Neural Operators ( Poster ) > link | Haydn Maust · Zongyi Li · Yixuan Wang · Anima Anandkumar 🔗 |
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HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing ( Poster ) > link | Tianlong Chen · Chengyue Gong · Daniel Diaz · Xuxi Chen · Jordan Wells · Qiang Liu · Zhangyang Wang · Andrew Ellington · Alex Dimakis · Adam Klivans 🔗 |
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Generating counterfactual explanations of tumor spatial proteomes to discover effective, combinatorial therapies that enhance cancer immunotherapy ( Poster ) > link | Jerry Wang · Matt Thomson 🔗 |
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Proposal of a topology-aware method to segment 3D plant tissues images. ( Poster ) > link | Minh On · Nicolas Boutry · Jonathan Fabrizio 🔗 |
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Structure-Aware Antibiotic Resistance Classification using Graph Neural Networks ( Poster ) > link | Aymen Qabel · Sofiane ENNADIR · Giannis Nikolentzos · Johannes Lutzeyer · Michail Chatzianastasis · Henrik Boström · Michalis Vazirgiannis 🔗 |
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MoleculeCLIP: Learning Transferable Molecule Multi-Modality Models via Natural Language ( Poster ) > link | Shengchao Liu · Weili Nie · Chengpeng Wang · Jiarui Lu · Zhuoran Qiao · Ling Liu · Jian Tang · Anima Anandkumar · Chaowei Xiao 🔗 |
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A 3D-Shape Similarity-based Contrastive Approach to Molecular Representation Learning ( Poster ) > link | Austin Atsango · Nathaniel Diamant · Ziqing Lu · Tommaso Biancalani · Gabriele Scalia · Kangway Chuang 🔗 |
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Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations ( Poster ) > link | Xiang Fu · Zhenghao Wu · Wujie Wang · Tian Xie · Sinan Keten · Rafael Gomez-Bombarelli · Tommi Jaakkola 🔗 |
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Predicting Drug-Drug Interactions using Deep Generative Models on Graphs ( Poster ) > link | Khang Ngo · Truong Son Hy · Risi Kondor 🔗 |
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Spatio-Temporal Weathering Predictions in the Sparse Data Regime with Gaussian Processes ( Poster ) > link | Giovanni De Felice · Vladimir Gusev · John Goulermas · Michael Gaultois · Matthew Rosseinsky · Catherine Gauvin 🔗 |
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An AI-Assisted Labeling Tool for Cataloging High-Resolution Images of Galaxies ( Poster ) > link | Gustavo Perez · Sean Linden · Timothy McQuaid · Matteo Messa · Daniela Calzetti · Subhransu Maji 🔗 |
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Mind the Retrosynthesis Gap: Bridging the divide between Single-step and Multi-step Retrosynthesis Prediction ( Poster ) > link | Alan Kai Hassen · Paula Torren-Peraire · Samuel Genheden · Jonas Verhoeven · Mike Preuss · Igor Tetko 🔗 |
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Zero or Infinite Data? Knowledge Synchronized Machine Learning Emulation ( Poster ) > link | Xihaier Luo · Wei Xu · Yihui Ren · Shinjae Yoo · Balu Nadiga · Ahsan Kareem 🔗 |
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Representation Learning to Effectively Integrate and Interpret Omics Data ( Poster ) > link | Sara Masarone 🔗 |
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Loop Unrolled Shallow Equilibrium Regularizer (LUSER) - A Memory-Efficient Inverse Problem Solver ( Poster ) > link | Peimeng Guan · Jihui Jin · Justin Romberg · Mark Davenport 🔗 |
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Re-Evaluating Chemical Synthesis Planning Algorithms ( Poster ) > link | Austin Tripp · Krzysztof Maziarz · Sarah Lewis · Guoqing Liu · Marwin Segler 🔗 |
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Thoughts on the Applicability of Machine Learning to Scientific Discovery and Possible Future Research Directions (Perspective) ( Poster ) > link | Shiro Takagi 🔗 |
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Substructure-Atom Cross Attention for Molecular Representation Learning ( Poster ) > link | Jiye Kim · Seungbeom Lee · Dongwoo Kim · Sungsoo Ahn · Jaesik Park 🔗 |
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Interdisciplinary Discovery of Nanomaterials Based on Convolutional Neural Networks ( Poster ) > link | Tong Xie · Yuwei Wan · Weijian Li · Qingyuan Linghu · Shaozhou Wang · Yalun Cai · Chunyu Kit · Han Liu · Clara Grazian · Bram Hoex 🔗 |
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Using Sum-Product Networks to estimate neural population stutcture in the brain ( Poster ) > link | Koosha Khalvati · Samantha Johnson · Stefan Mihalas · Michael Buice 🔗 |
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Chemistry Insights for Large Pretrained GNNs ( Poster ) > link | Janice Lan · Katherine Xu 🔗 |
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Deconvolution of Astronomical Images with Deep Neural Networks ( Poster ) > link | Hong Wang · Sreevarsha Sreejith · Yuewei Lin · Nesar Ramachandra · Anže Slosar · Shinjae Yoo 🔗 |
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Adaptive Bias Correction for Improved Subseasonal Forecast ( Poster ) > link | Soukayna Mouatadid · Paulo Orenstein · Genevieve Flaspohler · Judah Cohen · Miruna Oprescu · Ernest Fraenkel · Lester Mackey 🔗 |
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Learning Controllable Adaptive Simulation for Multi-scale Physics ( Poster ) > link | Tailin Wu · Takashi Maruyama · Qingqing Zhao · Gordon Wetzstein · Jure Leskovec 🔗 |
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Learning Efficient Hybrid Particle-continuum Representations of Non-equilibrium N-body Systems ( Poster ) > link |
11 presentersTailin Wu · Michael Sun · Hsuan-Gu Chou · Pranay Reddy Samala · Sithipont Cholsaipant · Sophia Kivelson · Jacqueline Yau · Rex Ying · E. Paulo Alves · Jure Leskovec · Frederico Fiuza |
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Toward Neural Network Simulation of Variational Quantum Algorithms ( Poster ) > link | Oliver Knitter · James Stokes · Shravan Veerapaneni 🔗 |
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Privileged Deep Symbolic Regression ( Poster ) > link | Luca Biggio · Tommaso Bendinelli · Pierre-alexandre Kamienny 🔗 |
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Simulation-Based Parallel Training ( Poster ) > link | Lucas Meyer · Alejandro Ribes · Bruno Raffin 🔗 |
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Fourier Neural Operator for Plasma Modelling ( Poster ) > link | Vignesh Gopakumar · Stanislas Pamela · Lorenzo Zanisi · Zongyi Li · Anima Anandkumar 🔗 |
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Standardization of chemical compounds using language modeling ( Poster ) > link | Miruna Cretu · Alessandra Toniato · Alain C. Vaucher · Amol Thakkar · Amin Debabeche · Teodoro Laino 🔗 |
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Learning Spatially-Aware Representations of Transcriptomic Data via Transfer Learning ( Poster ) > link | Minsheng Hao · Lei Wei · Xuegong Zhang 🔗 |
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Predicting electrolyte solution properties by combining neural network accelerated molecular dynamics and continuum solvent theory. ( Poster ) > link | Timothy T Duignan · Junji Zhang · Joshua Pagotto 🔗 |
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An Empirical Evaluation of Zeroth-Order Optimization Methods on AI-driven Molecule Optimization ( Poster ) > link | Elvin Lo · Pin-Yu Chen 🔗 |
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Data-Driven Computational Imaging for Scientific Discovery ( Poster ) > link | Andrew Olsen · Yolanda Hu · Vidya Ganapati 🔗 |
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De novo PROTAC design using graph-based deep generative models ( Poster ) > link | Divya Nori · Connor Coley · Rocío Mercado 🔗 |
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Conditional Invariances for Conformer Invariant Protein Representations ( Poster ) > link | Balasubramaniam Srinivasan · Vassilis Ioannidis · Soji Adeshina · Mayank Kakodkar · George Karypis · Bruno Ribeiro 🔗 |
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RLCG: When Reinforcement Learning Meets Coarse Graining ( Poster ) > link | Shenghao Wu · Tianyi Liu · Zhirui Wang · Wen Yan · Yingxiang Yang 🔗 |
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Neurosymbolic Programming for Science ( Poster ) > link | Jennifer J Sun · Megan Tjandrasuwita · Atharva Sehgal · Armando Solar-Lezama · Swarat Chaudhuri · Yisong Yue · Omar Costilla Reyes 🔗 |
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DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking ( Poster ) > link | Gabriele Corso · Hannes Stärk · Bowen Jing · Regina Barzilay · Tommi Jaakkola 🔗 |
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D-CIPHER: Discovery of Closed-form Partial Differential Equations ( Poster ) > link | Krzysztof Kacprzyk · Zhaozhi Qian · Mihaela van der Schaar 🔗 |
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Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction ( Poster ) > link | Junwen Bai · Yuanqi Du · Yingheng Wang · Shufeng Kong · John Gregoire · Carla Gomes 🔗 |
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Symbolic-Model-Based Reinforcement Learning ( Poster ) > link | Pierre-alexandre Kamienny · Sylvain Lamprier 🔗 |
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Towards Learned Simulators for Cell Migration ( Poster ) > link | Koen Minartz · Yoeri Poels · Vlado Menkovski 🔗 |
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Flow Annealed Importance Sampling Bootstrap ( Poster ) > link | Laurence Midgley · Vincent Stimper · Gregor Simm · Bernhard Schölkopf · José Miguel Hernández-Lobato 🔗 |
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Supervised Pretraining for Molecular Force Fields and Properties Prediction ( Poster ) > link | Xiang Gao · Weihao Gao · Wenzhi Xiao · Zhirui Wang · Chong Wang · Liang Xiang 🔗 |
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Learning Regularized Positional Encoding for Molecular Prediction ( Poster ) > link | Xiang Gao · Weihao Gao · Wenzhi Xiao · Zhirui Wang · Chong Wang · Liang Xiang 🔗 |
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Continuous PDE Dynamics Forecasting with Implicit Neural Representations ( Poster ) > link | Yuan Yin · Matthieu Kirchmeyer · Jean-Yves Franceschi · Alain Rakotomamonjy · Patrick Gallinari 🔗 |
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Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction ( Poster ) > link | Wenlin Chen · Austin Tripp · José Miguel Hernández-Lobato 🔗 |
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Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations ( Poster ) > link | Yingtao Luo · Qiang Liu · Yuntian Chen · Wenbo Hu · TIAN TIAN · Jun Zhu 🔗 |
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Chemistry Guided Molecular Graph Transformer ( Poster ) > link | Peisong Niu · Tian Zhou · Qingsong Wen · Liang Sun · Tao Yao 🔗 |
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Retrosynthesis Prediction Revisited ( Poster ) > link | Hongyu Tu · Shantam Shorewala · Tengfei Ma · Veronika Thost 🔗 |
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Optimizing Intermediate Representations of Generative Models for Phase Retrieval ( Poster ) > link | Tobias Uelwer · Sebastian Konietzny · Stefan Harmeling 🔗 |
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Bayesian parameter inference of a vortically perturbed flame model for the prediction of thermoacoustic instability ( Poster ) > link | Max Croci · Joel Vasanth · Ushnish Sengupta · Ekrem Ekici · Matthew Juniper 🔗 |