Publications | Research

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ICML

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2025

GenMol: A Drug Discovery Generalist with Discrete Diffusion

Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Yuxing Peng, Saee Paliwal, Weili Nie, Arash Vahdat

ICML

Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow

Zhonglin Cao, Mario Geiger, Allan Dos Santos Costa, Danny Reidenbach, Karsten Kreis, Tomas Geffner, Franco Pellegrini, Guoqing Zhou, Emine Kucukbenli

ICML

SLIM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression

Mohammad Mozaffari , Amir Yazdanbakhsh, Maryam Mehri Dehnavi

ICML

Score Distillation Sampling for Audio: Source Separation, Synthesis, and Beyond

Jessie Richter-Powell, Antonio Torralba, Jonathan Lorraine

ICML

Multi-student Diffusion Distillation for Better One-step Generators

Yanke Song, Jonathan Lorraine, Weili Nie, Karsten Kreis, James Lucas

ICML

SoftTreeMax: Policy Gradient via tree expansion

Gal Dalal, Assaf Hallak, Gugan Thoppe, Shie Mannor, Gal Chechik

ICML

2023

Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models

Wenhao Ding, Gerry Che, Ding Zhao, Marco Pavone

ICML

Global Context Vision Transformers

Ali Hatamizadeh, Hongxu Danny Yin, Greg Heinrich, Jan Kautz, Pavlo Molchanov

ICML

Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere

Boris Bonev, Thorsten Kurth, Christian Hundt, Jaideep Pathak, Maximilian Baust, Karthik Kashinath, Anima Anandkumar

ICML

Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models

Wenhao Ding, Tong Che, Ding Zhao, Marco Pavone

ICML

Equivariant Architectures for Learning in Deep Weight Spaces

Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron

ICML