Workshop
AI for Accelerated Materials Design (AI4Mat-2023)
Santiago Miret · Benjamin Sanchez-Lengeling · Jennifer Wei · Vineeth Venugopal · Marta Skreta · N M Anoop Krishnan
Room 228 - 230
Fri 15 Dec, 6:15 a.m. PST
The AI for Accelerated Materials Discovery (AI4Mat) Workshop 2023 provides an inclusive and collaborative platform where AI researchers and material scientists converge to tackle the cutting-edge challenges in AI-driven materials discovery and development. Our goal is to foster a vibrant exchange of ideas, breaking down barriers between disciplines and encouraging insightful discussions among experts from diverse disciplines and curious newcomers to the field. The workshop embraces a broad definition of materials design encompassing matter in various forms, such as crystalline and amorphous solid-state materials, glasses, molecules, nanomaterials, and devices. By taking a comprehensive look at automated materials discovery spanning AI-guided design, synthesis and automated material characterization, we hope to create an opportunity for deep, thoughtful discussion among researchers working on these interdisciplinary topics, and highlight ongoing challenges in the field.
Schedule
Fri 6:15 a.m. - 6:30 a.m.
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Opening Remarks
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Opening Remarks
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SlidesLive Video |
Santiago Miret · Benjamin Sanchez-Lengeling · Jennifer Wei · Vineeth Venugopal · Marta Skreta · N M Anoop Krishnan 🔗 |
Fri 6:30 a.m. - 6:45 a.m.
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Sim2Mat Lightning Talk - Rama Vasudevan
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Invited Talk
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SlidesLive Video |
Rama K Vasudevan 🔗 |
Fri 6:45 a.m. - 7:00 a.m.
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Sim2Mat Lightning Talk - Maria Chan
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Invited Talk
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SlidesLive Video |
Maria Chan 🔗 |
Fri 7:00 a.m. - 7:15 a.m.
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Sim2Mat Lightning Talk - Vijay Narasimhan
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Invited Talk
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SlidesLive Video |
Vijay Narasimhan 🔗 |
Fri 7:15 a.m. - 7:40 a.m.
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Sim2Mat Lightning Talk Panel
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Panel Q&A
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SlidesLive Video |
Rama K Vasudevan · Maria Chan · Vijay Narasimhan 🔗 |
Fri 7:40 a.m. - 7:50 a.m.
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MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling
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Spotlight
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SlidesLive Video |
Kin Long Kelvin Lee · Carmelo Gonzales · Marcel Nassar · Matthew Spellings · Michael Galkin · Santiago Miret 🔗 |
Fri 7:50 a.m. - 8:00 a.m.
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Investigating extrapolation and low-data challenges via contrastive learning of chemical compositions
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Spotlight
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SlidesLive Video |
Federico Ottomano · Giovanni De Felice · Rahul Savani · Vladimir Gusev · Matthew Rosseinsky 🔗 |
Fri 8:00 a.m. - 8:30 a.m.
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Coffee Break
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Fri 8:30 a.m. - 8:40 a.m.
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Exploring Organic Syntheses through Natural Language
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Spotlight
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SlidesLive Video |
Andres M Bran · Cheng-Hua Huang · Philippe Schwaller 🔗 |
Fri 8:40 a.m. - 8:50 a.m.
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ExPT: Synthetic Pretraining for Few-Shot Experimental Design
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Spotlight
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SlidesLive Video |
Tung Nguyen · Sudhanshu Agrawal · Aditya Grover 🔗 |
Fri 8:50 a.m. - 9:00 a.m.
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Accelerated Sampling of Rare Events using a Neural Network Bias Potential
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Spotlight
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SlidesLive Video |
Xinru Hua · Rasool Ahmad · Jose Blanchet · Wei Cai 🔗 |
Fri 9:00 a.m. - 9:10 a.m.
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Learning Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy
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Spotlight
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SlidesLive Video |
11 presentersMax Schwarzer · Jesse Farebrother · Joshua Greaves · Kevin Roccapriore · Ekin Dogus Cubuk · Rishabh Agarwal · Aaron Courville · Marc Bellemare · Sergei Kalinin · Igor Mordatch · Pablo Samuel Castro |
Fri 9:10 a.m. - 9:20 a.m.
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Message Passing Neural Network for Predicting Dipole Moment Dependent Core Electron Excitation Spectra
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Spotlight
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SlidesLive Video |
Kiyou Shibata · Teruyasu Mizoguchi 🔗 |
Fri 9:20 a.m. - 9:30 a.m.
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Reflection-Equivariant Diffusion for 3D Structure Determination from Isotopologue Rotational Spectra in Natural Abundance
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Spotlight
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SlidesLive Video |
Austin Cheng · Alston Lo · Santiago Miret · Brooks Pate · Alan Aspuru-Guzik 🔗 |
Fri 9:30 a.m. - 10:00 a.m.
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Emerald Cloud Labs Keynote - Jason Wallace
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Invited Talk
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Jason Wallace 🔗 |
Fri 10:00 a.m. - 12:00 p.m.
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Poster Session
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Poster Session
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Fri 12:00 p.m. - 1:00 p.m.
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Fireside Chat on LLMs for Materials Design
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Fireside Chat
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SlidesLive Video |
Andrew White · Gowoon Cheon · Gabe Gomes 🔗 |
Fri 1:00 p.m. - 1:30 p.m.
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Coffee Break
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Fri 1:30 p.m. - 1:40 p.m.
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Fine-Tuned Language Models Generate Stable Inorganic Materials as Text
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Spotlight
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SlidesLive Video |
Nate Gruver · Anuroop Sriram · Andrea Madotto · Andrew Wilson · Larry Zitnick · Zachary Ulissi 🔗 |
Fri 1:40 p.m. - 1:50 p.m.
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HoneyBee: Progressive Instruction Finetuning of Large Language Models for Materials Science
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Spotlight
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SlidesLive Video |
Yu Song · Santiago Miret · Huan Zhang · Bang Liu 🔗 |
Fri 1:50 p.m. - 2:00 p.m.
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Capturing Formulation Design of Battery Electrolytes with Chemical Large Language Model
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Spotlight
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SlidesLive Video |
Eduardo Soares · Vidushi Sharma · Emilio Vital Brazil · Renato Cerqueira · Young-Hye Na 🔗 |
Fri 2:00 p.m. - 2:10 p.m.
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Scalable Diffusion for Materials Generation
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Spotlight
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SlidesLive Video |
Sherry Yang · KwangHwan Cho · Amil Merchant · Pieter Abbeel · Dale Schuurmans · Igor Mordatch · Ekin Dogus Cubuk 🔗 |
Fri 2:10 p.m. - 2:20 p.m.
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Discovery of Novel Reticular Materials for Carbon Dioxide Capture using GFlowNets
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Spotlight
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SlidesLive Video |
Flaviu Cipcigan · Jonathan Booth · Rodrigo Neumann Barros Ferreira · Carine Dos Santos · Mathias Steiner 🔗 |
Fri 2:20 p.m. - 2:30 p.m.
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Graph-to-String Variational Autoencoder for Synthetic Polymer Design
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Spotlight
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SlidesLive Video |
Gabriel Vogel · Paolo Sortino · Jana M. Weber 🔗 |
Fri 2:30 p.m. - 2:40 p.m.
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Crystal-GFN: sampling materials with desirable properties and constraints
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Spotlight
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SlidesLive Video |
Mistal · Alex Hernandez-Garcia · Alexandra Volokhova · ALEXANDRE DUVAL · Yoshua Bengio · Divya Sharma · Pierre Luc Carrier · Michał Koziarski · Victor Schmidt 🔗 |
Fri 2:40 p.m. - 2:50 p.m.
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EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations
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Spotlight
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SlidesLive Video |
Vaibhav Bihani · UTKARSH PRATIUSH · Sajid Mannan · Tao Du · Zhimin Chen · Santiago Miret · Matthieu Micoulaut · Morten Smedskjaer · Sayan Ranu · N M Anoop Krishnan 🔗 |
Fri 2:50 p.m. - 3:00 p.m.
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Machine learning force field ranking of candidate solid electrolyte interphase structures in Li-ion batteries
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Spotlight
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SlidesLive Video |
James Stevenson 🔗 |
Fri 3:00 p.m. - 3:10 p.m.
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Learning Interatomic Potentials at Multiple Scales
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Spotlight
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SlidesLive Video |
Xiang Fu · Albert Musaelian · Anders Johansson · Tommi Jaakkola · Boris Kozinsky 🔗 |
Fri 3:10 p.m. - 3:30 p.m.
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Closing Remarks
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Closing Remarks
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SlidesLive Video |
Santiago Miret · Benjamin Sanchez-Lengeling · Jennifer Wei · Vineeth Venugopal · Marta Skreta · N M Anoop Krishnan 🔗 |
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A Bayesian Approach to Designing Microstructures and Processing Pathways for Tailored Material Properties ( Poster ) > link | Adam Generale · Conlain Kelly · Grayson Harrington · Andreas Robertson · Michael Buzzy · Surya Kalidindi 🔗 |
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Beyond Chemical Language: A Multimodal Approach to Enhance Molecular Property Prediction ( Poster ) > link | Eduardo Soares · Emilio Vital Brazil · Karen Fiorella Gutierrez · Renato Cerqueira · Daniel Sanders · Kristin Schmidt · Dmitry Zubarev 🔗 |
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Phonon predictions with E(3)-equivariant graph neural networks ( Poster ) > link | Shiang Fang · Mario Geiger · Joseph Checkelsky · Tess Smidt 🔗 |
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MTENCODER: A Multi-task Pretrained Transformer Encoder for Materials Representation Learning ( Poster ) > link | Thorben Prein · Elton Pan · Tom Doerr · Elsa Olivetti · Jennifer Rupp 🔗 |
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Data Efficient Training for Materials Property Prediction Using Active Learning Querying ( Poster ) > link | Carmelo Gonzales · Kin Long Kelvin Lee · Bin Mu · Michael Galkin · Santiago Miret 🔗 |
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Reconstructing Materials Tetrahedron: Challenges in Materials Information Extraction ( Poster ) > link | Kausik Hira · Mohd Zaki · Dhruvil Sheth · Mausam · N M Anoop Krishnan 🔗 |
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CoNO: Complex Neural Operator for Continuous Dynamical Systems ( Poster ) > link | Karn Tiwari · N M Anoop Krishnan · Prathosh AP 🔗 |
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Tokenizer Effect on Functional Material Prediction: Investigating Contextual Word Embeddings for Knowledge Discovery ( Poster ) > link | Tong Xie · Yuwei Wan · Ke Lu · Wenjie Zhang · Chunyu Kit · Bram Hoex 🔗 |
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On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions ( Poster ) > link | Alvaro Carbonero · ALEXANDRE DUVAL · Victor Schmidt · Santiago Miret · Alex Hernandez-Garcia · Yoshua Bengio · David Rolnick 🔗 |
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Out of Domain Stress Prediction on a Dataset of Simulated 3D Polycrystalline Microstructures ( Poster ) > link | Thomas Lu · Aarti Singh 🔗 |
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CURATOR: Autonomous Batch Active-Learning Workflow for Catalysts ( Poster ) > link | Xin Yang · Renata Sechi · Martin Petersen · Arghya Bhowmik · Heine A. Hansen 🔗 |
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Accurate Prediction of Experimental Band Gaps from Large Language Model-Based Data Extraction ( Poster ) > link | Samuel Yang · Shutong Li · Subhashini Venugopalan · Vahe Tshitoyan · Muratahan Aykol · Amil Merchant · Ekin Dogus Cubuk · Gowoon Cheon 🔗 |
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Self-supervised Crack Detection in X-ray Computed Tomography Data of Additive Manufacturing Parts ( Poster ) > link | Saber Nemati · Seyedeh Shaghayegh Rabbanian · Hao Wang · Leslie Butler · Shengmin Guo 🔗 |
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Active learning for excited states dynamics simulations to discover molecular degradation pathways ( Poster ) > link | Chen Zhou · Prashant Kumar · Daniel Escudero · Pascal Friederich 🔗 |
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Data Distillation for Neural Network Potentials toward Foundational Dataset ( Poster ) > link | Gang Seob Jung · Sangkeun Lee · Jong Choi 🔗 |
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Symbolic Learning for Material Discovery ( Poster ) > link | Daniel Cunnington · Flaviu Cipcigan · Rodrigo Neumann Barros Ferreira · Jonathan Booth 🔗 |
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Connectivity Optimized Nested Line Graph Networks for Crystal Structures ( Poster ) > link | Robin Ruff · Patrick Reiser · Jan Stühmer · Pascal Friederich 🔗 |
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LLM Drug Discovery Challenge: A Contest as a Feasibility Study on the Utilization of Large Language Models in Medicinal Chemistry ( Poster ) > link | Kusuri Murakumo · Naruki Yoshikawa · Kentaro Rikimaru · Shogo Nakamura · Kairi Furui · Takamasa Suzuki · Hiroyuki Yamasaki · Yuki Nishigaya · Yuzo Takagi · Masahito Ohue 🔗 |
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Search Strategies for Self-driving Laboratories with Pending Experiments ( Poster ) > link | Hao Wen · Jakob Zeitler · Connor Rupnow 🔗 |
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Gotta be SAFE: A new Framework for Molecular Design ( Poster ) > link | Emmanuel Noutahi · Cristian Gabellini · Michael Craig · Jonathan Siu Chi Lim · Prudencio Tossou 🔗 |
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Eco-Comp: Towards Responsible Computing in Materials Science ( Poster ) > link | Sai S Lingampalli · El Tayeb Bentria · Fadwa El Mellouhi 🔗 |
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Hierarchical GFlowNet for Crystal Structure Generation ( Poster ) > link | Tri Nguyen · Sherif Abdulkader Tawfik Abbas · Truyen Tran · Sunil Gupta · Santu Rana · Svetha Venkatesh 🔗 |
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Demonstrating ChemGymRL: An Interactive Framework for Reinforcement Learning for Digital Chemistry ( Poster ) > link | Chris Beeler · Sriram Ganapathi · Colin Bellinger · Mark Crowley · Isaac Tamblyn 🔗 |
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MatKG-2: Unveiling precise material science ontology through autonomous committees of LLMs ( Poster ) > link | Vineeth Venugopal · Elsa Olivetti 🔗 |
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MOFDiff: Coarse-grained Diffusion for Metal-Organic Framework Design ( Poster ) > link | Xiang Fu · Tian Xie · Andrew Rosen · Tommi Jaakkola · Jake Smith 🔗 |
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Learning the Language of NMR: Structure Elucidation from NMR spectra using Transformer Models ( Poster ) > link | Marvin Alberts · Federico Zipoli · Alain C. Vaucher 🔗 |
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Impacts of Data and Models on Unsupervised Pre-training for Molecular Property Prediction ( Poster ) > link | Elizabeth Coda · Gihan Panapitiya · Emily Saldanha 🔗 |
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Automatic Generation of Mechanistic Pathways of Organic Reactions with Dual Templates ( Poster ) > link | SHU-AN CHEN · Ramil Babazade · Yousung Jung 🔗 |
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Learning Conditional Policies for Crystal Design Using Offline Reinforcement Learning ( Poster ) > link | Prashant Govindarajan · Santiago Miret · Jarrid Rector-Brooks · Mariano Phielipp · Janarthanan Rajendran · Sarath Chandar 🔗 |
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Understanding Experimental Data by Identifying Symmetries with Deep Learning ( Poster ) > link | Yichen Guo · Shuyu Qin · Joshua Agar 🔗 |
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Evaluating AI-guided Design for Scientific Discovery ( Poster ) > link | Michael Pekala · Elizabeth Pogue · Alexander New · Gregory Bassen · Janna Domenico · Tyrel McQueen · Christopher Stiles 🔗 |
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Multi-objective Evolutionary Design of Microstructures using Diffusion Autoencoders ( Poster ) > link | Anirudh Suresh · Devesh Shah · Alemayehu Solomon Admasu · Devesh Upadhyay · Kalyanmoy Deb 🔗 |
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High throughput decomposition of spectra ( Poster ) > link | Dumitru Mirauta · Vladimir Gusev 🔗 |
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Searching for High-Value Molecules Using Reinforcement Learning and Transformers ( Poster ) > link | Raj Ghugare · Santiago Miret · Adriana Hugessen · Mariano Phielipp · Glen Berseth 🔗 |
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AdsorbRL: Deep Multi-Objective Reinforcement Learning for Inverse Catalysts Design ( Poster ) > link | Romain Lacombe · Khalid El-Awady 🔗 |
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AnisoGNN: physics-informed graph neural networks that generalize to anisotropic properties of polycrystals ( Poster ) > link | Guangyu Hu · Marat Latypov 🔗 |
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Automated Diffraction Pattern Analysis for Identifying Crystal Systems Using Multiview Opinion Fusion Machine Learning ( Poster ) > link | Jie Chen · Hengrui Zhang · Carolin Wahl · Wei Liu · Chad Mirkin · Vinayak Dravid · Daniel Apley · Wei Chen 🔗 |
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Haldane Bundles: A Dataset for Learning to Predict the Chern Number of Line Bundles on the Torus ( Poster ) > link | Cody Tipton · Elizabeth Coda · Davis Brown · Alyson Bittner · Caitlin Hutten · Grayson Jorgenson · Tegan Emerson · Henry Kvinge 🔗 |
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Rapid Fitting of Band-Excitation Piezoresponse Force Microscopy Using Physics Constrained Unsupervised Neural Networks ( Poster ) > link | Alibek T Kaliyev · Shuyu Qin · Yichen Guo · Seda Memik · Michael Mahoney · Amir Gholami · Nhan Tran · Martin Takac · Joshua Agar 🔗 |
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MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network ( Poster ) > link | Akihiro Kishimoto · Hiroshi Kajino · Hirose Masataka · Junta Fuchiwaki · Indra Priyadarsini S · Lisa Hamada · Hajime Shinohara · Daiju Nakano · Seiji Takeda 🔗 |
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Tree-based Quantile Active Learning for automated discovery of MOFs ( Poster ) > link | Ashna Jose · Emilie Devijver · Roberta Poloni · Valérie Monbet · Noel Jakse 🔗 |
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CLCS : Contrastive Learning between Compositions and Structures for practical Li-ion battery electrodes design ( Poster ) > link | Jaewan Lee · Changyoung Park · Hongjun Yang · Sehui Han · Woohyung Lim 🔗 |
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Combinatorial Optimization via Memory Metropolis: Template Networks for Proposal Distributions in Simulated Annealing applied to Nanophotonic Inverse Design ( Poster ) > link | Marlon Becker · Marco Butz · David Lemli · Carsten Schuck · Benjamin Risse 🔗 |
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Multi-modal Foundation Model for Material Design ( Poster ) > link | Seiji Takeda · Indra Priyadarsini S · Akihiro Kishimoto · Hajime Shinohara · Lisa Hamada · Hirose Masataka · Junta Fuchiwaki · Daiju Nakano 🔗 |
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Inverse-design of organometallic catalysts with guided equivariant diffusion ( Poster ) > link | François Cornet · Bardi Benediktsson · Bjarke Hastrup · Arghya Bhowmik · Mikkel Schmidt 🔗 |
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Latent Conservative Objective Models for Data-Driven Crystal Structure Prediction ( Poster ) > link | Han Qi · Stefano Rando · XINYANG GENG · Iku Ohama · Aviral Kumar · Sergey Levine 🔗 |
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Towards equilibrium molecular conformation generation with GFlowNets ( Poster ) > link | Alexandra Volokhova · Michał Koziarski · Alex Hernandez-Garcia · Chenghao Liu · Santiago Miret · Pablo Lemos · Luca Thiede · Zichao Yan · Alan Aspuru-Guzik · Yoshua Bengio 🔗 |
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Extremely Noisy 4D-TEM Strain Mapping Using Cycle Consistent Spatial Transforming Autoencoders ( Poster ) > link | Shuyu Qin · Joshua Agar · Nhan Tran 🔗 |
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A Generative Model for Accelerated Inverse Modelling Using a Novel Embedding for Continuous Variables ( Poster ) > link | Sébastien Bompas · Stefan Sandfeld 🔗 |
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Active Causal Machine Learning for Molecular Property Prediction ( Poster ) > link | Zachary Fox · Ayana Ghosh 🔗 |
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rvesimulator: An automated representative volume element simulator for data-driven material discovery ( Poster ) > link | Jiaxiang Yi · Miguel Bessa 🔗 |
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Unveiling the Secrets of $^1$H-NMR Spectroscopy: A Novel Approach Utilizing Attention Mechanisms ( Poster ) > link | Oliver Schilter · Marvin Alberts · Federico Zipoli · Philippe Schwaller · Alain C. Vaucher · Teodoro Laino 🔗 |
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Distributed Reinforcement Learning for Molecular Design: Antioxidant case ( Poster ) > link | Huanyi Qin · Denis Akhiyarov · Kenneth Chiu · Mauricio Araya-Polo 🔗 |
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Accelerated Modelling of Interfaces for Electronic Devices using Graph Neural Networks ( Poster ) > link | Pratik Brahma · Krishnakumar Bhattaram · Sayeef Salahuddin 🔗 |
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Extracting a Database of Challenges and Mitigation Strategies for Sodium-ion Battery Development ( Poster ) > link | Mrigi Munjal · Thorben Prein · Vineeth Venugopal · Kevin Huang · Elsa Olivetti 🔗 |
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Deep inverse design of hydrophobic patches on DNA origami for mesoscale assembly of superlattices ( Poster ) > link | Po-An Lin · Simiao Ren · Jonathan Piland · Leslie Collins · Stefan Zauscher · Yonggang Ke · Gaurav Arya 🔗 |
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CoDBench: A Critical Evaluation of Data-driven Models for Continuous Dynamical Systems ( Poster ) > link | Priyanshu Burark · Karn Tiwari · Meer Mehran Rashid · Prathosh AP · N M Anoop Krishnan 🔗 |
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BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics ( Poster ) > link | Suresh Bishnoi · Jayadeva Dr · Sayan Ranu · N M Anoop Krishnan 🔗 |