38 citations · 62 across the 11 of their papers we have counts for
11 papers
MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property Prediction
Carl Edwards, Ziqing Lu, Ehsan Hajiramezanali +3
Bridging biomolecular modeling with natural language information, particularly through large language models (LLMs), has recently emerged as a promising interdisciplinary research…
Cell Morphology-Guided Small Molecule Generation with GFlowNets
Stephen Zhewen Lu, Ziqing Lu, Ehsan Hajiramezanali +4
High-content phenotypic screening, including high-content imaging (HCI), has gained popularity in the last few years for its ability to characterize novel therapeutics without prio…
Understanding Reinforcement Learning-Based Fine-Tuning of Diffusion Models: A Tutorial and Review
Masatoshi Uehara, Yulai Zhao, Tommaso Biancalani +1
This tutorial provides a comprehensive survey of methods for fine-tuning diffusion models to optimize downstream reward functions. While diffusion models are widely known to provid…
Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control
Masatoshi Uehara, Yulai Zhao, Kevin Black +6
Diffusion models excel at capturing complex data distributions, such as those of natural images and proteins. While diffusion models are trained to represent the distribution in th…
Conformalized Deep Splines for Optimal and Efficient Prediction Sets
Nathaniel Diamant, Ehsan Hajiramezanali, Tommaso Biancalani +1
Uncertainty estimation is critical in high-stakes machine learning applications. One effective way to estimate uncertainty is conformal prediction, which can provide predictive inf…
Towards Understanding and Improving GFlowNet Training
Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali +3
Generative flow networks (GFlowNets) are a family of algorithms that learn a generative policy to sample discrete objects with non-negative reward . Learning objectives g…