[NeurIPS Best Paper] 1000 Layer Networks for Self-Supervised RL — Kevin Wang et al, Princeton
Kevin Wang and his team from Princeton discuss their NeurIPS Best Paper on scaling reinforcement learning networks to 1,000 layers deep. They explain how self-supervised RL and architectural innovations like residual connections and layer normalization allowed them to achieve…