Audio effect modeling with Deep Learning using Pytorch and synthetic dataset generation with Pedalboard

Applying Machine Learning Techniques To Assess Whether A Country’s Currency Can Predict The Movement Of Their Respective Stock Market Index

self-supervised learning, deep learning, representation learning, RotNet, temporal convolutional network(TCN), deformation transformation, sketch pre-train, sketch classification, sketch retrieval, free-hand sketch, official code of paper "Deep Self-Supervised Representation Learning for Free-Hand Sketch"

ETH Zürich Semester Project exploring the possibilities of using Deep Learning to extract vital signs from Radar Data

This repository contains code and resources for a project focused on predicting traffic volume using Temporal Convolutional Networks (TCNs). Leveraging the Metro Interstate Traffic Volume dataset from 2012-2018, the project aims to develop an accurate model for short- to medium-term traffic volume forecasting in Minneapolis-St Paul, MN.

Temporal Convolutions for Multi-Step Quadrotor Motion Prediction

Multivariate time series analysis on london bike sharing dataset

Build end-to-end Deep Neural Network to translate speech to text (ASR model)

PyTorch implementation of Temporal Convolutional Network

comprehensive collection of powerful techniques for time series data visualization, analysis and modeling

Continuous Estimation of Human Joint Angles From sEMG Using a Multi-Feature Temporal Convolutional Attention-Based Network

Action Classification on Breakfast Dataset using Temporal Convolutional Networks (TCN)

Undergraduate group project in which we built an ECG classifier using a TCN-CNN with 97% accuracy

Source code (train/test) accompanying the paper entitled "Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach" in CVPR 2019 (https://arxiv.org/abs/1903.10764).

Temporal Convolutional Network for Sequence Modelling

The repository has the PyTorch codes to reproduce the results for our recently accepted paper, "Estimation of Acoustic Impedance from Seismic Data using Temporal Convolutional Network", in SEG Technical Program Expanded Abstracts, 2019.

This repo contains an implementation code for the weakly supervised surgical tool tracker. In this research, the temporal dependency in surgical video data is modeled using a convolutional LSTM which is trained only on image level labels to detect, localize and track surgical instruments.

TinyOdom: Hardware-Aware Efficient Neural Inertial Navigation

A Deep Graph Neural Network Architecture for Modelling Spatio-temporal Dynamics in rs-fMRI Data

Modelling Spring Reverb with Neural Audio Effects