Research Notebooks

Key Ideas From
Important Papers

Sharing articles and tutorials on the finer details of training and tuning deep neural networks for maximum performance.

2024-04-10 optimization

Contrastive Language-Image Pretraining

Connecting text and images.

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2024-04-06 optimization

Mode Connectivity

Local minima in loss landscapes are connected by high accuracy pathways.

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2024-03-24 regularization optimization

AutoAugment

Learning optimal transformation pipelines for data augmentation.

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2024-03-19 optimization

Gradient Boosting

Ensembles where new members are trained to correct previous mistakes.

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2024-03-08 compression

Knowledge Distillation

Training a small model on the outputs of a larger and more accurate model.

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2024-02-26 optimization

Double Descent

A phenomena where generalization gets worse then better with larger models and bigger datasets.

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2024-02-15 optimization generation

Denoising Diffusion

A class of generative latent variable models inspired by nonequilibrium thermodynamics.

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2024-01-29 compression

Optimal Brain Damage

An early method for pruning networks according to parameter saliency.

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2024-01-22 optimization transfer

Low-Rank Adaptation

Reducing the storage requirements for fine tuned task specific networks.

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2024-01-21 optimization ensemble

Snapshot Ensembles

A low-cost method that leverages checkpoints throughout the training trajectory.

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2024-01-20 optimization reinforcement

Proximal Policy Optimization

A computationally efficient on-policy reinforcement learning algorithm.

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2024-01-19 optimization neuroevolution

Natural Evolution Strategies

A family of algorithms for evolving the parameters of search distributions.

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2024-01-18 regularization

Dropout

Masking random neurons on each forward pass during training.

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2024-01-17 optimization reinforcement

World Models

Dreaming with generative models of reinforcement learning environments.

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2024-01-16 optimization reinforcement

Deep Q-Learning

A foundational off-policy algorithm that kickstarted deep reinforcement learning.

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2024-01-14 optimization

Stochastic Weight Averaging

An optimization trick for the final phases of training with SGD.

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2024-01-13 compression

Lottery Ticket Hypothesis

Finding sparse subnetworks that train as well as dense networks from scratch.

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2024-01-13 optimization reinforcement

Trust Region Policy Optimization

The monotonic on-policy reinforcement learning algorithm.

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all attention augmentation bayesian classification clustering diffusion distillation efficient embedding ensemble evolution federated generative interpretability latent optimization pruning quantization regression regularization reinforcement segmentation sparsity supervised theory transfer tuning unsupervised