This repository contains the code for our upcoming paper An Investigation of End-to-End Models for Robust Speech Recognition at ICASSP 2021.
Safe robot learning
self-driving using end-to-end state space models
A deep learning-powered visual navigation engine to enables autonomous navigation of pocket-size quadrotor - running on PULP
State Representations as Incentives for Reinforcement Learning Agents: A Sim2Real Analysis on Robotic Grasping
An end-to-end (E2E) reinforcement learning model for autonomous vehicle collision avoidance in the CARLA simulator, using a recurrent PPO algorithm for dynamic control. The model processes RGB camera inputs to make real-time acceleration and steering decisions.
This repo contains data and code for Task-Aware Machine Unlearning with Application to Load Forecasting.
This is the official repo for the paper E2E-AT: A Unified Framework for Tackling Uncertainty in Task-aware End-to-end Learning, to be appeared in AAAI-24.
Code for PaperRobot: Incremental Draft Generation of Scientific Ideas
Data Scientist - Machine Learning Engineer Tutorial
DCFNet: Discriminant Correlation Filters Network for Visual Tracking
this repository hosts my master's thesis codes and dataset.
A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.
Self-Driving Car Behavioral Cloning based End-to-End learning, Computer Vision & Deep Neural Network
Deep Unfolding Network for Image Super-Resolution (CVPR, 2020) (PyTorch)
Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems
The Space Resorts sample capsule demonstrates a fully-developed capsule that uses several of the features and abilities discussed in the Bixby Developer Guides, while also using the best practices described in the Bixby Design Guides.
Weakly Supervised End-to-End Learning (NeurIPS 2021)
Evolutionary Graph Pattern Learner that learns SPARQL queries for a given set of source-target-pairs from an endpoint.
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