The original implementation of TNDM used in the NeurIPS 2021 paper (no longer being updated)

Overview

TensorFlow Requirement: 1.x TensorFlow 2 Not Supported

TNDM - Targeted Neural Dynamical Modeling

Note: This code is no longer being updated. The official re-implementation can be found at: https://github.com/HennigLab/tndm.

The code in this repository implements the models used in the Neurips 2021 paper, "Targeted Neural Dynamical Modeling". It also houses code from the baseline model, "Latent Factor Analysis via Dynamical Systems" (borrowed from https://github.com/lfads/models/tree/master/research/lfads). Latent dynamics models have emerged as powerful tools for modeling and interpreting neural population activity. Recently, there has been a focus on incorporating simultaneously measured behaviour into these models to further disentangle sources of neural variability in their latent space. These approaches, however, are limited in their ability to capture the underlying neural dynamics (e.g. linear) and in their ability to relate the learned dynamics back to the observed behaviour (e.g. no time lag). To this end, we introduce Targeted Neural Dynamical Modeling (TNDM), a nonlinear state-space model that jointly models the neural activity and external behavioural variables. TNDM decomposes neural dynamics into behaviourally relevant and behaviourally irrelevant dynamics; the relevant dynamics are used to reconstruct the behaviour through a flexible linear decoder and both sets of dynamics are used to reconstruct the neural activity through a linear decoder with no time lag. We implement TNDM as a sequential variational autoencoder and validate it on recordings taken from the premotor and motor cortex of a monkey performing a center-out reaching task. We show that TNDM is able to learn low-dimensional latent dynamics that are highly predictive of behaviour without sacrificing its fit to the neural data.

Prerequisites

The code is written in Python 2.7.6. The other prerequisites are:

Getting started

Before starting, run the following:

$ export PYTHONPATH=$PYTHONPATH:/path/to/your/directory/tndm_paper/

where "path/to/your/directory" is replaced with the path to the tndm_paper repository (you can get this path by using the pwd command). This allows the nested directories to access modules from their parent directory.

Train an TNDM model

For a full list of flags, their descriptions, and their default values, refer to the top of run_tndm_double.py. We trained all of our models using the run_tndm_double_paper.sh bash script which allows for modifying important values.

Finally, you can view the results in the tndm_eval_matt_data-M1.ipynb file.

๐Ÿ’ƒ VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena

๐Ÿ’ƒ VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena.

Heidelberg-NLP 17 Nov 07, 2022
Demonstrational Session git repo for H SAF User Workshop (28/1)

5th H SAF User Workshop The 5th H SAF User Workshop supported by EUMeTrain will be held in online in January 24-28 2022. This repository contains inst

H SAF 4 Aug 04, 2022
Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields.

This repository contains the code release for Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields. This implementation is written in JAX, and is a fork of Google's JaxNeRF

Google 625 Dec 30, 2022
ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation

ClevrTex This repository contains dataset generation code for ClevrTex benchmark from paper: ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi

Laurynas Karazija 26 Dec 21, 2022
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

Thalles Silva 1.7k Dec 28, 2022
Predicting Event Memorability from Contextual Visual Semantics

Predicting Event Memorability from Contextual Visual Semantics

0 Oct 06, 2021
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision

The Official PyTorch Implementation of DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision

Shiyi Lan 3 Oct 15, 2021
Learning Synthetic Environments and Reward Networks for Reinforcement Learning

Learning Synthetic Environments and Reward Networks for Reinforcement Learning We explore meta-learning agent-agnostic neural Synthetic Environments (

AutoML-Freiburg-Hannover 16 Sep 02, 2022
TDmatch is a Python library developed to perform matching tasks in three categories:

TDmatch TDmatch is a Python library developed to perform matching tasks in three categories: Text to Data which matches tuples of a table to text docu

Naser Ahmadi 5 Aug 11, 2022
๐Ÿค– A Python library for learning and evaluating knowledge graph embeddings

PyKEEN PyKEEN (Python KnowlEdge EmbeddiNgs) is a Python package designed to train and evaluate knowledge graph embedding models (incorporating multi-m

PyKEEN 1.1k Jan 09, 2023
Code for MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks

MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks This is the code for the paper: MentorNet: Learning Data-Driven Curriculum fo

Google 302 Dec 23, 2022
A computational optimization project towards the goal of gerrymandering the results of a hypothetical election in the UK.

A computational optimization project towards the goal of gerrymandering the results of a hypothetical election in the UK.

Emma 1 Jan 18, 2022
Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks

Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks Work accepted at NeurIPS'21 [paper, video]. If you use this code in

TU Delft 43 Dec 07, 2022
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

Introduction QRec is a Python framework for recommender systems (Supported by Python 3.7.4 and Tensorflow 1.14+) in which a number of influential and

Yu 1.4k Dec 30, 2022
A curated (most recent) list of resources for Learning with Noisy Labels

A curated (most recent) list of resources for Learning with Noisy Labels

Jiaheng Wei 321 Jan 09, 2023
This is an implementation of PIFuhd based on Pytorch

Open-PIFuhd This is a unofficial implementation of PIFuhd PIFuHD: Multi-Level Pixel-Aligned Implicit Function forHigh-Resolution 3D Human Digitization

Lingteng Qiu 235 Dec 19, 2022
Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch

Lie Transformer - Pytorch (wip) Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch. Only the SE3 version will be present in thi

Phil Wang 78 Oct 26, 2022
ใ€ŒPyTorch Implementation of AnimeGANv2ใ€ใ‚’็”จใ„ใฆใ€็”Ÿๆˆใ—ใŸ้ก”็”ปๅƒใ‚’ๅ…ƒใฎ็”ปๅƒใซไธŠๆ›ธใใ™ใ‚‹ใƒ‡ใƒข

AnimeGANv2-Face-Overlay-Demo PyTorch Implementation of AnimeGANv2ใ‚’็”จใ„ใฆใ€็”Ÿๆˆใ—ใŸ้ก”็”ปๅƒใ‚’ๅ…ƒใฎ็”ปๅƒใซไธŠๆ›ธใใ™ใ‚‹ใƒ‡ใƒขใงใ™ใ€‚

KazuhitoTakahashi 21 Oct 18, 2022
Repository for Multimodal AutoML Benchmark

Benchmarking Multimodal AutoML for Tabular Data with Text Fields Repository for the NeurIPS 2021 Dataset Track Submission "Benchmarking Multimodal Aut

Xingjian Shi 44 Nov 24, 2022
Alpha-Zero - Telegram Group Manager Bot Written In Python Using Pyrogram

โœจ Alpha Zero Bot โœจ Telegram Group Manager Bot + Userbot Written In Python Using

1 Feb 17, 2022