ICML 2024PastAI for scienceTheory
ICML'24 Workshop ML for Life and Material Science: From Theory to Industry Applications
ML4LMS
- Submission deadline
- May 23, 2024, 23:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (68)
Fetched from OpenReview (v2) on 2026-06-10.
A Bayesian Approach to Adversarially Robust Life Testing
A generative foundation model for antibody sequence understanding
A Recipe for Charge Density Prediction
AbFlex: Predicting the conformational flexibility of antibody CDRs
Accelerating the inference of string generation-based chemical reaction models for industrial applications
Analysis of Atom-level pretraining with QM data for Graph Neural Networks Molecular property models
Augmenting Evolutionary Models with Structure-based Retrieval
Batch-effect invariant graph neural networks for predicting chemotherapy response in triple-negative breast cancer patients
Benchmarking probabilistic machine learning in protein fitness landscape predictions
Cell Morphology-Guided Small Molecule Generation with GFlowNets
CellFlows: Inferring Splicing Kinetics from Latent and Mechanistic Cellular Dynamics
Chemical Language Modeling with Structured State Spaces
Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms
CodonMPNN for Organism Specific and Codon Optimal Inverse Folding
Combining Graph Attention and Recurrent Neural Networks in a Variational Autoencoder for Molecular Representation Learning and Drug Design
Constructing artificial life and materials scientists with accelerated AI using Deep AndersoNN
Deep Supramolecular Language Processing for Co-crystal Prediction
Detecting critical treatment effect bias in small subgroups
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
DualBind: A Dual-Loss Framework for Protein-Ligand Binding Affinity Prediction
Energy-Free Guidance of Geometric Diffusion Models for 3D Molecule Inverse Design
Enhancing Multi-Tip Artifact Detection in STM Images Using Fourier Transform and Vision Transformers
Equivariant Flow Matching for Molecular Conformer Generation
EvoSBDD: Latent Evolution for Accurate and Efficient Structure-Based Drug Design
Exploring sequence landscape of biosynthetic gene clusters with protein language models
Finding Structure-Property Relationships for Molecular Property Predictions with Globally Explainable AI
Flexible Docking via Unbalanced Flow Matching
FlowBack: A Flow-matching Approach for Generative Backmapping of Macromolecules
From Laboratory to Everyday Life: Personalized Stress Prediction via Smartwatches
Future-proof vaccine design with a generative model of antibody cross-reactivity
Gene-centric evaluation of causal variant prediction for DNA models
Generalizing Microscopy Image Labeling via Layer-Matching Adversarial Domain Adaptation
Generative acceleration of molecular dynamics simulations for solid-state electrolytes
Generative Modeling of Molecular Dynamics Trajectories
Graph-Based Retriever Captures the Long Tail of Biomedical Knowledge
GraphKAN: Graph Kolmogorov Arnold Network for Small Molecule-Protein Interaction Predictions
Hierarchical Contrastive Learning for Enzyme Function Prediction
Hyperspectral Unmixing for Raman Spectroscopy via Physics-Constrained Autoencoders
Improving Fragment-Based Deep Molecular Generative Models
Improving Molecular Modeling with Geometric GNNs: an Empirical Study
Improving Performance Prediction of Electrolyte Formulations with Transformer-based Molecular Representation Model
Improving Route Development Using Convergent Retrosynthesis Planning
Latent-Guided Equivariant Diffusion for Controlled Structure-Based De Novo Ligand Generation
Likelihood-based fine-tuning of protein language models for few-shot fitness prediction and design
Limitations of scRNA-seq Zero-Imputation Methods for Network Inference
Machine learning nominal max oxygen consumption from wearable reflective pulse oximetry with density functional theory
Mirror, Mirror on the Wall: Automating Dental Smile Analysis in Smart Mirrors with CNN and Diffusion Model
Multi-Modal and Multi-Task Transformer for Small Molecule Drug Discovery
Multi-Objective Guidance via Importance Sampling for Target-Aware Diffusion-based De Novo Ligand Generation
Navigating Trustworthiness of Deep Learning in ∆∆G prediction : Addressing Data Bias, Model Evaluation, and Interpretation
On the Effectiveness of Quantum Chemistry Pre-training for Pharmacological Property Prediction
Out-of-Distribution Validation for Bioactivity Prediction in Drug Discovery: Lessons from Materials Science
PLINDER: The protein-ligand interactions dataset and evaluation resource
PLUTO: Pathology-Universal Transformer
Predicting metal-protein interactions using cofolding methods: Status quo
Protein language models expose viral mimicry and immune escape
Protein Language Models in Directed Evolution
Quality-Diversity for One-Shot Biological Sequence Design
RamanSPy: Augmenting Raman Spectroscopy Data Analysis with AI
Reducing Uncertainty through Mutual Information in Structural and Systems Biology
RGFN: Synthesizable Molecular Generation Using GFlowNets
Robustness of Explainable Artificial Intelligence in Industrial Process Modelling
Scanning Tunneling Microscopy (STM) Image Segmentation Using Unsupervised and Few-shot Learning
Score-Based Generative Models For Binding Peptide Backbones
Scoreformer: A Surrogate Model For Large-Scale Prediction of Docking Scores
Structural activity prediction models recover known binding modes (Poster abstract)
TAGMol: Target-Aware Gradient-guided Molecule Generation
Towards Linking Graph Topology to Model Performance for Biomedical Knowledge Graph Completion