Publications

Kale-ab Tessera, Chiratidzo Matowe, Arnu Pretorius, Benjamin Rosman, Sara Hooker (2022). Just-in-Time Sparsity: Learning Dynamic Sparsity Schedules. Dynamic Neural Networks ICML Workshop 2022.

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Ibrahim Salihu Yusuf, Kale-ab Tessera, Thomas Tumiel, Zohra Slim, Amine Kerkeni, Sella Nevo, Arnu Pretorius (2021). On pseudo-absence generation and machine learning for locust breeding ground prediction in Africa. AI + HADR 2021 and ML4D 2021 NeurIPS Workshops.

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Arnu Pretorius, Kale-ab Tessera, Andries P. Smit, Claude Formanek, St John Grimbly, Kevin Eloff, Siphelele Danisa, Lawrence Francis, Jonathan Shock, Herman Kamper, Willie Brink, Herman Engelbrecht, Alexandre Laterre, Karim Beguir (2021). Mava: a research framework for distributed multi-agent reinforcement learning.

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Kale-ab Tessera, Sara Hooker, Benjamin Rosman (2021). Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization. Sparsity in Neural Networks Workshop 2021.

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Kale-ab Tessera (2021). On Sparsity In Deep Learning: The Benefits And Pitfalls Of Sparse Neural Networks And How To Learn Their Architectures. Faculty of Science, University of the Witwatersrand.

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