Machine Learning Reseach Flashcards

Machine Learning Research Flashcards is a collection of flashcards associated with scientific research papers in the field of machine learning. Best used with Anki. Edit MLRF on GitHub.

Accurate, Large Minibatch SGD

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Anchor Pruning for Object Detection

Attention Is All You Need

Barlow Twins

Barlow Twins: Self-Supervised Learning via Redundancy Reduction

Batch Normalization

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

Deep Reinforcement Learning

Playing Atari with Deep Reinforcement Learning

DETR

DETR: End-to-End Object Detection with Transformers

Dice Loss

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

Diffusion Models

Dilated Convolutions

Multi-Scale Context Aggregation by Dilated Convolution

Distilling the Knowledge in a Neural Network

DUSt3R

DUSt3R: Geometric 3D Vision Made Easy

Gaussian Splatting

3D Gaussian Splatting for Real-Time Radiance Field Rendering

Instant-NGP

Instant Neural Graphics Primitives with a Multiresolution Hash Encoding

Latent Diffusion Models

High-Resolution Image Synthesis with Latent Diffusion Models

Learned Thresholds Token Merging and Pruning for Vision Transformers

LoRA

Low-Rank Adaptation of Large Language Models

Mip-NeRF

Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields

Mip-NeRF 360

Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields

Mixture-of-Experts with Expert Choice Routing

MobileNetV1

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

MobileNetV2

MobileNetV2: Inverted Residuals and Linear Bottlenecks

NeRF

NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

Once-for-All

Once-for-All: Train One Network and Specialize it for Efficient Deployment

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Proximal Policy Optimization Algorithms

RetinaNet

Focal Loss for Dense Object Detection

Segment Anything

SETR

Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

SimCLR

A Simple Framework for Contrastive Learning of Visual Representations

Squeeze-and-Excitation Networks

SSD: Single Shot MultiBox Detector

Stable Diffusion

High-Resolution Image Synthesis with Latent Diffusion Models

Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity

The Lottery Ticket Hypothesis

The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Token Merging: Your ViT But Faster

Variational Auto-Encoder

Auto-Encoding Variational Bayers

Vision Transformers

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale