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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
Project Page [ Contact: ai4sciencecommunity@gmail.com ]

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Schedule

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