AI Maker Community - Weekly Paper Readings

• Adam: A Method for Stochastic Optimization Deep Learning

• A Guide to Convolution Arithmetic for Deep Learning Deep Learning Computer Vision

• Algorithms for Hyper-parameter Optimization Machine Learning Theory

• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Computer Vision, Deep Learning

• Attention is All You Need NLP, Deep Learning

• Auto-encoding Variational Bayes Deep Learning

• Axiomatic Attribution for Deep Networks Deep Learning, Computer Vision

• Bag of Tricks for Image Classification with Convolutional Neural Networks Computer Vision, Deep Learning

• Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Deep Learning

• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding NLP, Deep Learning

• Binarized Neural Networks Deep Learning

• Communication-Efficient Learning of Deep Networks from Decentralized Data Deep Learning, Machine Learning Theory

• Confident Learning: Estimating Uncertainty in Dataset Labels Machine Learning Theory

• Cyclical Learning Rates for Training Neural Networks Deep Learning

• Deep Residual Networks for Image Recognition Computer Vision, Deep Learning

• Direct Preference Optimization: Your Language Model is Secretly a Reward Model Reinforcement Learning, NLP

• Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Deep Learning, Machine Learning Theory

• Dropout: A Simple Way to Prevent Neural Networks from Overfitting Deep Learning

• Focal Loss for Dense Object Detection Computer Vision, Deep Learning

• FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness Deep Learning

• Generative Adversarial Networks Deep Learning

• Genie: Generative Interactive Environments Reinforcement Learning

• Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Computer Vision, Deep Learning

• Graph Neural Networks: A Review of Methods and Applications Deep Learning

• Hidden Technical Debt in Machine Learning Systems MLOps Machine Learning Theory

• High Resolution Image Synthesis with Latent Diffusion Models Computer Vision, Deep Learning

• ImageNet Classification with Deep Convolutional Networks Computer Vision, Deep Learning

• Language Models are Few-Shot Learners NLP, Deep Learning

• Learning Deep Features for Discriminative Localization Computer Vision, Deep Learning

• Learning Transferable Visual Models From Natural Language Supervision Computer Vision, NLP, Deep Learning

• LightGBM: A Highly Efficient Gradient Boosting Decision Tree Machine Learning Theory

• LLama2: Open Foundation and Fine-Tuned Chat Models NLP, Deep Learning

• LoRA: Low-Rank Adaptation of Large Language Models NLP, Deep Learning

• Long Short-Term Memory Deep Learning

• Long-form Factuality in Large Language Models NLP, Deep Learning

• MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution NLP, Deep Learning

• Mamba: Linear-Time Sequence Modeling with Selective State Spaces Deep Learning

• Mask R-CNN Computer Vision, Deep Learning

• No-Free Lunch Theorems for Optimization Machine Learning Theory

• Panoptic Segmentation Computer Vision, Deep Learning

• Playing Atari with Deep Reinforcement Learning Reinforcement Learning

• QLoRA: Efficient Finetuning of Quantized LLMs Deep Learning, NLP

• ReAct: Synergizing Reasoning and Acting in Language Models NLP, Reinforcement Learning

• Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks NLP, Deep Learning

• RWKV: Reinventing RNNs for the Transformer Era Deep Learning

• Segment Anything Computer Vision, Deep Learning

• The Algorithmic Foundations of Differential Privacy Machine Learning Theory

• The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective Machine Learning Theory

• The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits NLP, Deep Learning

• The M6 forecasting competition: Bridging the gap between forecasting and investment decisions Machine Learning Theory

• The Matrix Calculus You Need for Deep Learning Deep Learning

• Training Compute-Optimal Large Language Models Deep Learning

• U-Net: Convolutional Networks for Biomedical Image Segmentation Computer Vision, Deep Learning

• Visualizing and Understanding Convolutional Networks Computer Vision, Deep Learning

• When Do Neural Nets Outperform Boosted Trees on Tabular Data? Deep Learning, Machine Learning Theory