RylanSchaeffer

NeurIPS-2022-No-Free-Lunch

Code for NeurIPS 2022 No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit

ecs198-cryptocurrency-technologies

FieteLab-Dynamical-CRP

Code for CoLLAs 2022 paper Streaming Inference for Infinite Nonstationary Clustering

FieteLab-RIBP

Code for ICML 2022 paper Streaming Inference for Infinite Feature Models

FieteLab-Sorscher-2022-Reproduction

(Partial) Code for preprint: Disentangling Fact from Grid Cell Fiction in Trained Deep Path Integrators

HarvardAM207-prior-networks

Harvard Fall 2019 Applied Math 207 A Primer and Critique of Prior Networks

MIT2.152-Nonlinear-Control

MIT Spring 2020 Mechanical Engineering 2.152 Nonlinear Control (Professor Jean-Jacques Slotine)

Stanford-AI-Alignment-Double-Descent-Tutorial

Code for Arxiv Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle

Stanford-LaTeX-Poster-Template

Stanford LaTeX poster template

ucl-adv-dl-rl

RylanSchaeffer/Stanford-LaTeX-Poster-Template

Stanford LaTeX poster template

RylanSchaeffer/Stanford-AI-Alignment-Double-Descent-Tutorial

Code for Arxiv Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle

RylanSchaeffer/rylanschaeffer.github.io

RylanSchaeffer/FieteLab-Nonparametric-SwAV

PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882

RylanSchaeffer/FieteLab-RCRP

Code for UAI 2021 paper Efficient Online Inference for Nonparametric Mixture Models

RylanSchaeffer/hilbert

RylanSchaeffer/RepDistiller

[ICLR 2020] Contrastive Representation Distillation (CRD), and benchmark of recent knowledge distillation methods

RylanSchaeffer/FieteLab-Dynamical-CRP

Code for CoLLAs 2022 paper Streaming Inference for Infinite Nonstationary Clustering

RylanSchaeffer/FieteLab-RIBP

Code for ICML 2022 paper Streaming Inference for Infinite Feature Models

RylanSchaeffer/FieteLab-Sorscher-2022-Reproduction

(Partial) Code for preprint: Disentangling Fact from Grid Cell Fiction in Trained Deep Path Integrators

RylanSchaeffer/NeurIPS-2020-Reverse-Engineering-RNNs

Code for NeurIPS 2020 paper Reverse-engineering Recurrent Neural Network solutions to a hierarchical inference task for mice.

RylanSchaeffer/FieteLab-DP-Means-Plus-Plus

(Abandoned) Endowing DP-Means with K-Means++ Initialization

RylanSchaeffer/grid-pattern-formation

repository for Neurips 2019 publication code

RylanSchaeffer/helm

Holistic Evaluation of Language Models (HELM), a framework to increase the transparency of language models (https://arxiv.org/abs/2211.09110).

RylanSchaeffer/incontext-learning

Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"

RylanSchaeffer/KoyejoLab-Double-Descent-ICLR-2024-Blog

RylanSchaeffer/lm-evaluation-harness

A framework for few-shot evaluation of autoregressive language models.

RylanSchaeffer/lsl

Shaping Visual Representations with Language for Few-shot Classification, ACL 2020

RylanSchaeffer/naturecomm_cscg

RylanSchaeffer/papers-visualizations

Plotting data from papers to better understand results!

RylanSchaeffer/prismatic-vlms

A flexible and efficient codebase for training visually-conditioned language models (VLMs)

RylanSchaeffer/qambo

Experiments in Deep Q Learning controlling ambulance placement

RylanSchaeffer/sail-blog-no-free-lunch

The SAIL blog on No Free Lunch for Deep Learning in Neuroscience

RylanSchaeffer/simple_rl

A simple framework for experimenting with Reinforcement Learning in Python.

RylanSchaeffer/Stanford-CS-242-Programming-Languages

Repo for Stanford CS 242 Programming Languages Fall 2022 with Prof. Aikens

RylanSchaeffer/Stanford-CS-265-Rand-Algs

Repo for Stanford CS 265 Randomized Algorithms Fall 2022 with Prof. Wootters

RylanSchaeffer/three.js

JavaScript 3D Library.

RylanSchaeffer/torch_tem

Implementation of the Tolman Eichenbaum Machine in pytorch

RylanSchaeffer/transformers

🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.

RylanSchaeffer/webgl-examples

Code examples that accompany the MDN WebGL documentation