Taco Cohen
Taco Cohen is a deep learning researcher at FAIR specializing in code generation, reinforcement learning, equivariance, and generative models. He has contributed to AI research at Qualcomm, Scyfer, UvA, DeepMind, and OpenAI. His work on equivariant neural networks has advanced understanding of learning efficiency in machine learning models. Cohen maintains an active presence in the AI community through his research and public engagement.
Taco Cohen
Taco Cohen is a deep learning researcher at FAIR specializing in code generation, reinforcement learning, equivariance, and generative models. He has contributed to AI research at Qualcomm, Scyfer, UvA, DeepMind, and OpenAI. His work on equivariant neural networks has advanced understanding of learning efficiency in machine learning models. Cohen maintains an active presence in the AI community through his research and public engagement.