Robert LangeinTowards Data ScienceFour Deep Learning Papers to Read in January 2022From Bootstrapped Meta-Learning to Time Series Forecasting with Deep Learning, the Relationship between Extrapolation & Generalization and…Jan 10, 20223Jan 10, 20223
Robert LangeinTowards Data ScienceFour Deep Learning Papers to Read in December 2021From Sensory Substitution to Decision Transformers, Persistent Evolution Strategies and Sharpness-Aware MinimizationNov 28, 2021Nov 28, 2021
Robert LangeinTowards Data ScienceFour Deep Learning Papers to Read in September 2021From Auto-ML to Vision Transformer Training & Representations and Catastrophic Fisher ExplosionSep 4, 20212Sep 4, 20212
Robert LangeinTowards Data ScienceFour Deep Learning Papers to Read in August 2021From Optimizer Benchmarks to Network Dissection, Vision Transformers & Lottery SubspacesAug 2, 20212Aug 2, 20212
Robert LangeinTowards Data ScienceFour Deep Learning Papers to Read in July 2021From Large Scale Deep RL to Adversarial Robustness, SimCLR-v2 & Learning Neural Network SpacesJun 30, 20211Jun 30, 20211
Robert LangeinTowards Data ScienceFour Deep Learning Papers to Read in June 2021Jun 1, 20212Jun 1, 20212
Robert LangeinTowards Data ScienceFour Deep Learning Papers to Read in May 2021Apr 30, 20212Apr 30, 20212
Robert LangeinTowards Data ScienceFour Deep Learning Papers to Read in April 2021From Meta-Gradients to Clockwork VAEs, a Global Workspace Theory for Neural Networks and the Edge of Training StabilityxMar 30, 20211Mar 30, 20211
Robert LangeinTowards Data ScienceFour Deep Learning Papers to Read in March 2021From Synthetic Gradients to Capsule Networks, Conservation Laws for Network Training & Multi-Agent Generative ModelsFeb 28, 20214Feb 28, 20214
Robert LangeinTowards Data ScienceEvolving Neural Networks in JAXScaling CMA-ES with the Power of vmap and jitFeb 13, 2021Feb 13, 2021
