Research
Publications
/ 54
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mai 13th, 2025
Virtual Cells: Predict, Explain, Discover
Drug discovery is fundamentally a process of inferring the effects of treatments on patients, and would therefore benefit immensely from …
décembre 8th, 2024
Implicit Delta Learning of High Fidelity Neural Network Potentials
novembre 1st, 2024
QGFN: Controllable Greediness with Action Values
octobre 29th, 2024
ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation
octobre 26th, 2024
SAFE setup for generative molecular design
octobre 17th, 2024
Benchmarking Transcriptomics Foundation Models for Perturbation Analysis : one PCA still rules them all
octobre 14th, 2024
Graph Classification Gaussian Processes via Hodgelet Spectral Features
octobre 8th, 2024
Batched Bayesian optimization with correlated candidate uncertainties
octobre 4th, 2024
A call for an industry-led initiative to critically assess machine learning for real-world drug discovery
septembre 11th, 2024
On the Scalability of GNNs for Molecular Graphs
septembre 11th, 2024
Automated Discovery of Pairwise Interactions from Unstructured Data
septembre 10th, 2024
How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval
juin 10th, 2024
Graph Positional and Structural Encoder
juin 2nd, 2024
Learning to Scale Logits for Temperature-Conditional GFlowNets
mai 31st, 2024
Amortizing intractable inference in diffusion models for vision, language, and control
avril 2nd, 2024
Propensity Score Alignment for Unpaired Multimodal Data
mars 30th, 2024
Targeted Sequential Indirect Experiment Design
mars 27th, 2024
Discrete Probabilistic Inference as Control in Multi-path Environments
novembre 6th, 2023
DGFN: Double Generative Flow Networks
novembre 2nd, 2023
Generating QM1B with PySCFipu
octobre 30th, 2023
Role of Structural and Conformational Diversity for Machine Learning Potentials
octobre 27th, 2023
Latent Space Simulator for Unveiling Molecular Free Energy Landscapes and Predicting Transition Dynamics
octobre 18th, 2023
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
octobre 16th, 2023
Gotta be SAFE: A New Framework for Molecular Design
juillet 14th, 2023
Graph Positional and Structural Encoder
juin 7th, 2023
Goal-conditioned GFlowNets for Controllable Multi-Objective Molecular Design
juin 5th, 2023
Real-World Molecular Out-Of-Distribution: Specification and Investigation
mai 26th, 2023
UNSAT Solver Synthesis via Monte Carlo Forest Search
mai 11th, 2023
Towards Understanding and Improving GFlowNet Training
mars 6th, 2023
MoDTI: Modular Framework For Evaluating Inductive Biases in DTI Modeling
mars 6th, 2023
Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration
février 11th, 2023
Sequential Underspecified Instrument Selection for Cause-Effect Estimation
février 9th, 2023
Helixer–de novo Prediction of Primary Eukaryotic Gene Models Combining Deep Learning and a Hidden Markov Model
février 8th, 2023
DynGFN: Bayesian Dynamic Causal Discovery Using Generative Flow Networks
février 1st, 2023
GFlowNets for AI-driven Scientific Discovery
novembre 7th, 2022
Object-centric Causal Representation Learning
octobre 29th, 2022
Object-centric architectures enable efficient causal representation learning
octobre 23rd, 2022
Multi-Objective GFlowNets
septembre 26th, 2022
Learning GFlowNets From Partial Episodes for Improved Convergence and Stability
juillet 9th, 2022
Leveraging Structure Between Environments: Phylogenetic Regularization Incentivizes Disentangled Representations
juin 16th, 2022
Long Range Graph Benchmark
juin 2nd, 2022
Weakly Supervised Representation Learning with Sparse Perturbations
mai 25th, 2022
Recipe for a General, Powerful, Scalable Graph Transformer
octobre 29th, 2021
Properties From Mechanisms: an Equivariance Perspective on Identifiable Representation Learning
octobre 8th, 2021
3D Infomax improves GNNs for Molecular Property Prediction
octobre 4th, 2021
On the Robustness of Generalization of Drug–Drug Interaction Models
juin 7th, 2021
Rethinking Graph Transformers with Spectral Attention
décembre 16th, 2020
Helixer: Cross-species Gene Annotation of Large Eukaryotic Genomes Using Deep Learning
décembre 15th, 2020
Molecular Design in Synthetically Accessible Chemical Space via Deep Reinforcement Learning
octobre 6th, 2020
Directional Graph Networks
mai 16th, 2020
Geodesics in Fibered Latent Spaces: A Geometric Approach to Learning Correspondences Between Conditions
avril 12th, 2020
Principal Neighbourhood Aggregation for Graph Nets
mai 28th, 2019
Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling
mai 28th, 2019