Trajectory Variational Autoencder baseline for Multi-Agent Behavior challenge 2022

Overview

MABe_2022_TVAE: a Trajectory Variational Autoencoder baseline for the 2022 Multi-Agent Behavior challenge

This repository contains jupyter notebooks that implement a trajectory variational autoencoder (tVAE) baseline model for embedding the mouse and fly trajectory datasets for the 2022 Multi-Agent Behavior Challenge. Performance of these notebooks is as follows:

Dataset Mean F1 Mean MSE task F1 1 task F1 2 task F1 3 task F1 4 task F1 5
Mouse trajectories 0.121 0.095 0.339 0.479 0.021 0.491 x
Fly trajectories 0.291 x 0.0 0.0 0.0 0.388 0.539

Where the "task F1" values are F1 scores on specific sample evaluation tasks. Note, while this baseline is outperforming PCA for the mice, it actually does significantly worse than PCA for the flies! (Why? Who knows!)

How to use these notebooks

Clone this repository and open train_mouse_tvae.ipynb or train_fly_tvae.ipynb in a jupyter notebook session. Follow notebook instructions to make your own submission, then play with the model architecture and parameters inside the tvae directory to see if you are able to improve performance!

Note, you'll need to download the mouse and/or fly datasets into the provided mouse_data and fly_data directories to use this code.

Owner
Andrew Ulmer
Computer Technician in Ann Kennedy's Lab @ Northwestern
Andrew Ulmer
Single Image Deraining Using Bilateral Recurrent Network (TIP 2020)

Single Image Deraining Using Bilateral Recurrent Network Introduction Single image deraining has received considerable progress based on deep convolut

23 Aug 10, 2022
The Rich Get Richer: Disparate Impact of Semi-Supervised Learning

The Rich Get Richer: Disparate Impact of Semi-Supervised Learning Preprocess file of the dataset used in implicit sub-populations: (Demographic groups

<a href=[email protected]"> 4 Oct 14, 2022
Monocular 3D Object Detection: An Extrinsic Parameter Free Approach (CVPR2021)

Monocular 3D Object Detection: An Extrinsic Parameter Free Approach (CVPR2021) Yunsong Zhou, Yuan He, Hongzi Zhu, Cheng Wang, Hongyang Li, Qinhong Jia

Yunsong Zhou 51 Dec 14, 2022
Finite Element Analysis

FElupe - Finite Element Analysis FElupe is a Python 3.6+ finite element analysis package focussing on the formulation and numerical solution of nonlin

Andreas D. 20 Jan 09, 2023
Hierarchical Motion Encoder-Decoder Network for Trajectory Forecasting (HMNet)

Hierarchical Motion Encoder-Decoder Network for Trajectory Forecasting (HMNet) Our paper: https://arxiv.org/abs/2111.13324 We will release the complet

15 Oct 17, 2022
CARL provides highly configurable contextual extensions to several well-known RL environments.

CARL (context adaptive RL) provides highly configurable contextual extensions to several well-known RL environments.

AutoML-Freiburg-Hannover 51 Dec 28, 2022
AI-Fitness-Tracker - AI Fitness Tracker With Python

AI-Fitness-Tracker We have build a AI based Fitness Tracker using OpenCV and Pyt

Sharvari Mangale 5 Feb 09, 2022
Robust and Accurate Object Detection via Self-Knowledge Distillation

Robust and Accurate Object Detection via Self-Knowledge Distillation paper:https://arxiv.org/abs/2111.07239 Environments Python 3.7 Cuda 10.1 Prepare

Weipeng Xu 6 Jul 01, 2022
DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021)

Evaluation, Training, Demo, and Inference of DeFMO DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021) Denys Rozumnyi, Martin R. O

Denys Rozumnyi 139 Dec 26, 2022
Ejemplo Algoritmo Viterbi - Example of a Viterbi algorithm applied to a hidden Markov model on DNA sequence

Ejemplo Algoritmo Viterbi Ejemplo de un algoritmo Viterbi aplicado a modelo ocul

Mateo Velásquez Molina 1 Jan 10, 2022
Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.

Demonstration of OpenVINO techniques - Model-division and a simplest-way to support custom layers Description: Model Optimizer in Intel(r) OpenVINO(tm

Yasunori Shimura 12 Nov 09, 2022
Classification of ecg datas for disease detection

ecg_classification Classification of ecg datas for disease detection

Atacan ÖZKAN 5 Sep 09, 2022
Code for the ICCV'21 paper "Context-aware Scene Graph Generation with Seq2Seq Transformers"

ICCV'21 Context-aware Scene Graph Generation with Seq2Seq Transformers Authors: Yichao Lu*, Himanshu Rai*, Cheng Chang*, Boris Knyazev†, Guangwei Yu,

Layer6 Labs 37 Dec 18, 2022
LieTransformer: Equivariant Self-Attention for Lie Groups

LieTransformer This repository contains the implementation of the LieTransformer used for experiments in the paper LieTransformer: Equivariant Self-At

OxCSML (Oxford Computational Statistics and Machine Learning) 50 Dec 28, 2022
Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

Decision Transformer Lili Chen*, Kevin Lu*, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas†, and Igor M

Kevin Lu 1.4k Jan 07, 2023
Pytorch implementation of "Geometrically Adaptive Dictionary Attack on Face Recognition" (WACV 2022)

Geometrically Adaptive Dictionary Attack on Face Recognition This is the Pytorch code of our paper "Geometrically Adaptive Dictionary Attack on Face R

6 Nov 21, 2022
Source code to accompany Defunctland's video "FASTPASS: A Complicated Legacy"

Shapeland Simulator Source code to accompany Defunctland's video "FASTPASS: A Complicated Legacy" Download the video at https://www.youtube.com/watch?

TouringPlans.com 70 Dec 14, 2022
A fast model to compute optical flow between two input images.

DCVNet: Dilated Cost Volumes for Fast Optical Flow This repository contains our implementation of the paper: @InProceedings{jiang2021dcvnet, title={

Huaizu Jiang 8 Sep 27, 2021
[AAAI 2022] Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification

Sparse Structure Learning via Graph Neural Networks for inductive document classification Make graph dataset create co-occurrence graph for datasets.

16 Dec 22, 2022
Multi-Stage Episodic Control for Strategic Exploration in Text Games

XTX: eXploit - Then - eXplore Requirements First clone this repo using git clone https://github.com/princeton-nlp/XTX.git Please create two conda envi

Princeton Natural Language Processing 9 May 24, 2022