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Lil'Log

Harness Engineering for Self-Improvement Scaling Laws, Carefully Why We Think Reward Hacking in Reinforcement Learning Extrinsic Hallucinations in LLMs Diffusion Models for Video Generation Thinking about High-Quality Human Data Adversarial Attacks on LLMs LLM Powered Autonomous Agents Prompt Engineering The Transformer Family Version 2.0 Large Transformer Model Inference Optimization Some Math behind Neural Tangent Kernel Generalized Visual Language Models Learning with not Enough Data Part 3: Data Generation Learning with not Enough Data Part 2: Active Learning Learning with not Enough Data Part 1: Semi-Supervised Learning How to Train Really Large Models on Many GPUs? What are Diffusion Models? Contrastive Representation Learning Reducing Toxicity in Language Models Controllable Neural Text Generation How to Build an Open-Domain Question Answering System? Neural Architecture Search Exploration Strategies in Deep Reinforcement Learning The Transformer Family Curriculum for Reinforcement Learning Self-Supervised Representation Learning Evolution Strategies Meta Reinforcement Learning Are Deep Neural Networks Dramatically Overfitted? Generalized Language Models Object Detection Part 4: Fast Detection Models Meta-Learning: Learning to Learn Fast Flow-based Deep Generative Models From Autoencoder to Beta-VAE Attention? Attention! Implementing Deep Reinforcement Learning Models with Tensorflow + OpenAI Gym Policy Gradient Algorithms A (Long) Peek into Reinforcement Learning The Multi-Armed Bandit Problem and Its Solutions Object Detection for Dummies Part 3: R-CNN Family Object Detection for Dummies Part 2: CNN, DPM and Overfeat Object Detection for Dummies Part 1: Gradient Vector, HOG, and SS Learning Word Embedding Anatomize Deep Learning with Information Theory From GAN to WGAN How to Explain the Prediction of a Machine Learning Model? Predict Stock Prices Using RNN: Part 2 Predict Stock Prices Using RNN: Part 1 An Overview of Deep Learning for Curious People FAQ
Domain Randomization for Sim2Real Transfer
2019-05-05 · via Lil'Log
In Robotics, one of the hardest problems is how to make your model transfer to the real world. Due to the sam…