MLX: An array framework for Apple silicon

Matlab files with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz http:…

The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.

The MATH Dataset (NeurIPS 2021)

A algebraic word problem dataset, with multiple choice questions annotated with rationales.

Code for "Fast Context Adaptation via Meta-Learning"

Memory efficient MAML using gradient checkpointing

A PyTorch Library for Meta-learning Research

Code for COLING 2022 long paper: MetaPrompting: Learning to Learn Better Prompts

Neat implementation of Meta-SGD in pytorch: https://arxiv.org/abs/1707.09835

Neat and flexible implementation of MAML in pytorch: https://arxiv.org/abs/1703.03400

Platform for designing and evaluating Graph Neural Networks (GNN)

Google Cloud tutorial and setup

This repository contains implementations and illustrative code to accompany DeepMind publications

🌀 Stanford CS 228 - Probabilistic Graphical Models

State-of-the-Art Text Embeddings

an easy-to-use interface to fine-tuned BERT models for computing semantic similarity in clinical and web text. that's it.

A simple implementation of SimCSE

pytorch版simcse无监督语义相似模型

Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"

[EMNLP 2021] SimCSE: Simple Contrastive Learning of Sentence Embeddings https://arxiv.org/abs/2104.08821

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

Neumorphism designed Jekyll theme for personal websites, portfolios and resumes.