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PyTorch implementation of adversarial attacks [torchattacks]
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Implementation for Time Varying Recurrent Neural Networks (TV RNN)
Predictive coding networks for temporal prediction
Hands-On Graph Neural Networks Using Python, published by Packt
Saccade analysis within the Allen Institute Visual Coding Dataset.
We turn natural language descriptions of behaviors into machine-executable code
[TMLR 2023] V1T: Large-scale mouse V1 response prediction using a Vision Transformer
A Python API for working with Neurodata stored in the NWB Format
A scikit-learn compatible neural network library that wraps PyTorch
Introducing dendrites to spiking neural networks. Designed for the Brian 2 simulator.
A reservoir computing toolbox for neuroscientists
MoSeq2 Jupyter Notebook platform used to run all of the MoSeq2 tools in a GUI.
EXTRACT is a tractable and robust automated cell extraction tool for calcium imaging, which extracts the activities of cells as time series from both one-photon and two-photon calcium imaging movies.
Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA
links to conference publications in graph-based deep learning
A library for developing deep generative models in a more concise, intuitive and extendable way
Segment-Anything + 3D. Let's lift anything to 3D.
Hands-on tutorial on adversarial examples 😈. With Streamlit app ❤️.
A Docker image to provide web VNC interface to access Ubuntu LXDE/LxQT desktop environment.
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RN…
Model interpretability and understanding for PyTorch