Official implementation of MIRAGE, a multimodal encoding framework for predicting whole-brain fMRI responses with adaptive modality gating.

Repository for the "Discovering Functionally Selective Brain Regions with a Deep Topographic Multimodal Model" paper

TopoLM: brain-like spatio-functional organization in a topographic language model

Scaling Laws for Task-Optimized Models of the Primate Visual Ventral Stream, ICML 2025 Spotlight

Modeling cortical visual topography with interactive topographic network (ITN) models

Omnivore: A Single Model for Many Visual Modalities

Evaluate computational models on their alignment to behavioral and neural measurements in the domain of language

Techniques to reduce the numer of supervised synaptic updates (number of epochs x number of images x weights)) needed to train a artificial model of the brain,CORnet-S architecture.

Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(NeurIPS, 2021) paper

Scenic: A Jax Library for Computer Vision Research and Beyond

Lucid library adapted for PyTorch

Single Headed Attention RNN - "Stop thinking with your head"

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Turn Python scripts into handouts with Markdown and figures

arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv

Code for "Learning Perceptually-Aligned Representations via Adversarial Robustness"

NASBench: A Neural Architecture Search Dataset and Benchmark

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

Code for Task representations in neural networks trained to perform many cognitive tasks

contribute stimuli or data to BrainIO

TensorFlow code and pre-trained models for BERT

High Fidelity Simulator for Reinforcement Learning and Robotics Research.

The fastai deep learning library

N-D labeled arrays and datasets in Python

[NeurIPS'19 Oral] CORnet: Modeling the Neural Mechanisms of Core Object Recognition

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Robust Vision Benchmark