5 citations · 10 across the 4 of their papers we have counts for
4 papers
Generative Model for Small Molecules with Latent Space RL Fine-Tuning to Protein Targets
Ulrich A. Mbou Sob, Qiulin Li, Miguel Arbesú +3
A specific challenge with deep learning approaches for molecule generation is generating both syntactically valid and chemically plausible molecular string representations. To addr…
Should we be going MAD? A Look at Multi-Agent Debate Strategies for LLMs
Andries Smit, Paul Duckworth, Nathan Grinsztajn +2
Recent advancements in large language models (LLMs) underscore their potential for responding to inquiries in various domains. However, ensuring that generative agents provide accu…
Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX
Clément Bonnet, Daniel Luo, Donal Byrne +21
Open-source reinforcement learning (RL) environments have played a crucial role in driving progress in the development of AI algorithms. In modern RL research, there is a need for…
Mava: a research library for distributed multi-agent reinforcement learning in JAX
Ruan de Kock, Omayma Mahjoub, Sasha Abramowitz +5
Multi-agent reinforcement learning (MARL) research is inherently computationally expensive and it is often difficult to obtain a sufficient number of experiment samples to test hyp…