activity
20212025
most citedToward Collaborative Reinforcement Learning Agents that Communicate Through Text-Based Natural Language

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.QM2025

De novo peptide sequencing rescoring and FDR estimation with Winnow

Amandla Mabona, Jemma Daniel, Henrik Servais Janssen Knudsen +7

Machine learning has markedly advanced de novo peptide sequencing (DNS) for mass spectrometry-based proteomics. DNS tools offer a reliable way to identify peptides without relying…

eess.AS2022

TransFusion: Transcribing Speech with Multinomial Diffusion

Matthew Baas, Kevin Eloff, Herman Kamper

Diffusion models have shown exceptional scaling properties in the image synthesis domain, and initial attempts have shown similar benefits for applying diffusion to unconditional t…

cs.CL2021

Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channel

Kevin Eloff, Okko Räsänen, Herman A. Engelbrecht +2

Multi-agent reinforcement learning has been used as an effective means to study emergent communication between agents, yet little focus has been given to continuous acoustic commun…

cs.LG2021★ 3 cited

Toward Collaborative Reinforcement Learning Agents that Communicate Through Text-Based Natural Language

Kevin Eloff, Herman A. Engelbrecht

Communication between agents in collaborative multi-agent settings is in general implicit or a direct data stream. This paper considers text-based natural language as a novel form…

cs.LG2021★ 2 cited

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…