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Most implemented papers

Robust Adversarial Reinforcement Learning

lerrel/rllab-adv ICML 2017

Deep neural networks coupled with fast simulation and improved computation have led to recent successes in the field of reinforcement learning (RL).

Stochastic Gradient Hamiltonian Monte Carlo

JavierAntoran/Bayesian-Neural-Networks 17 Feb 2014

Hamiltonian Monte Carlo (HMC) sampling methods provide a mechanism for defining distant proposals with high acceptance probabilities in a Metropolis-Hastings framework, enabling more efficient exploration of the state space than standard random-walk proposals.

Automatic Latent Fingerprint Segmentation

luannd/MinutiaeNet 25 Apr 2018

We present a simple but effective method for automatic latent fingerprint segmentation, called SegFinNet.

Machine Learning and System Identification for Estimation in Physical Systems

baggepinnen/Robotlib.jl 5 Jun 2019

The main approach to estimation and learning adopted is optimization based.

DeepNeuro: an open-source deep learning toolbox for neuroimaging

QTIM-Lab/DeepNeuro 14 Aug 2018

Translating neural networks from theory to clinical practice has unique challenges, specifically in the field of neuroimaging.

Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning

ALRhub/action-conditional-rkn 20 Oct 2020

We adopt a recent probabilistic recurrent neural network architecture, called Re-current Kalman Networks (RKNs), to model learning by conditioning its transition dynamics on the control actions.

Learning Object Manipulation Skills from Video via Approximate Differentiable Physics

petrikvladimir/video_skills_learning_with_approx_physics 3 Aug 2022

We evaluate our approach on a 3D reconstruction task that consists of 54 video demonstrations sourced from 9 actions such as pull something from right to left or put something in front of something.

memorAIs: an Optical Character Recognition and Rule-Based Medication Intake Reminder-Generating Solution

FlyN-Nick/MemorAIs_Frontend 11 Dec 2023

Memory-based medication non-adherence is an unsolved problem that is responsible for considerable disease burden in the United States.

Preparing for the Unknown: Learning a Universal Policy with Online System Identification

vincentyu68/policy_transfer 8 Feb 2017

Together, UP-OSI is a robust control policy that can be used across a wide range of dynamic models, and that is also responsive to sudden changes in the environment.

Reinforcement Learning for Pivoting Task

LeoToledo/PivotingTaskRL 1 Mar 2017

In this work we propose an approach to learn a robust policy for solving the pivoting task.