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Features: Agents: DQN, Vanilla Policy Gradient, DDPG, PPO OpenAI Gym integration support both Discrete and Box environments Render (--render) and save (--record_video) environment replay Model-free asynchronous training (--num_workers)

Additional Features: Memory replay: Simple, Proportional Prioritized Experience Replay Modularized hyper-parameters setting (--hparams and hparams/defaults.py) Modularized action functions (action functions) and gradient update functions (compute gradient)

My first attempt at removing phones from the notorious mirror selfie using deep learning #TensorFlow #keras #AI #DeepLearning #selfie

Amazing first experience at #ijcai2019 presenting “Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings”, done with Sebastian Riedel (@[email protected]) Tim Rocktäschel Matko Bošnjak Pasquale Minervini Jun Wang. Thanks so much for the mentorship and support UCL Natural Language Processing! Wooooo! 🚀

Innovation Minds Engineering Camp First Session!