This repo contains different kinds of presentations that I was giving. Most of them are just paper presentations for a reading group (disclaimer: not all of them are good).

Papers covered (sorry for arxiv links instead of conferences ones):

• Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One
• FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
• Principled Weight Initialization for Hypernetworks
• Multiplicative Interactions and Where to Find Them
• SinGAN: Learning a Generative Model from a Single Natural Image
• Normalized and Geometry-Aware Self-Attention Network for Image Captioning
• XLNet: Generalized Autoregressive Pretraining for Language Understanding
• Large Scale GAN Training for High Fidelity Natural Image Synthesis
• Continual learning with hypernetworks
• Learning deep representations by mutual information estimation and maximization
• On the "steerability" of generative adversarial networks
• Non-Adversarial Image Synthesis with Generative Latent Nearest Neighbors
• What's Hidden in a Randomly Weighted Neural Network?
• Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
• Learning Implicit Generative Models by Matching Perceptual Features
• Learning Implicit Fields for Generative Shape Modeling
• Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO
• Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
• Normalized and Geometry-Aware Self-Attention Network for Image Captioning
• Pruning neural networks without any data by iteratively conserving synaptic flow
• The State of Sparsity in Deep Neural Networks
• Weight Agnostic Neural Networks
• ReZero is All You Need: Fast Convergence at Large Depth