Kale-ab Tessera

According to our database, Kale-ab Tessera authored at least 8 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Efficiently Quantifying Individual Agent Importance in Cooperative MARL.

Omayma Mahjoub, Ruan de Kock, Siddarth Singh, Wiem Khlifi, Abidine Vall, Kale-ab Tessera, Arnu Pretorius

CoRR, 2023

How much can change in a year? Revisiting Evaluation in Multi-Agent Reinforcement Learning.

Siddarth Singh, Omayma Mahjoub, Ruan de Kock, Wiem Khlifi, Abidine Vall, Kale-ab Tessera, Arnu Pretorius

CoRR, 2023

Generalisable Agents for Neural Network Optimisation.

Kale-ab Tessera, Callum Rhys Tilbury, Sasha Abramowitz, Ruan de Kock, Omayma Mahjoub, Benjamin Rosman, Sara Hooker, Arnu Pretorius

CoRR, 2023

Are we going MAD? Benchmarking Multi-Agent Debate between Language Models for Medical Q&A.

Andries P. Smit, Paul Duckworth, Nathan Grinsztajn, Kale-ab Tessera, Thomas D. Barrett, Arnu Pretorius

CoRR, 2023

Reduce, Reuse, Recycle: Selective Reincarnation in Multi-Agent Reinforcement Learning.

Claude Formanek, Callum Rhys Tilbury, Jonathan P. Shock, Kale-ab Tessera, Arnu Pretorius

CoRR, 2023

2021

On pseudo-absence generation and machine learning for locust breeding ground prediction in Africa.

Ibrahim Salihu Yusuf, Kale-ab Tessera, Thomas Tumiel, Sella Nevo, Arnu Pretorius

CoRR, 2021

Mava: a research framework for distributed multi-agent reinforcement learning.

Arnu Pretorius, Kale-ab Tessera, Andries P. Smit, Claude Formanek, St John Grimbly, Kevin Eloff, Siphelele Danisa, Lawrence Francis, Jonathan P. Shock, Herman Kamper, Willie Brink, Herman A. Engelbrecht, Alexandre Laterre, Karim Beguir

CoRR, 2021

Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization.

Kale-ab Tessera, Sara Hooker, Benjamin Rosman

CoRR, 2021