37 papers with code • 0 benchmarks • 0 datasets

This task has no description! Would you like to contribute one?

Most implemented papers

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

bioinf-jku/TTUR NeurIPS 2017

Generative Adversarial Networks (GANs) excel at creating realistic images with complex models for which maximum likelihood is infeasible.

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.

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.

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.

Identification of LTV Dynamical Models with Smooth or Discontinuous Time Evolution by means of Convex Optimization

baggepinnen/LTVModels.jl 27 Feb 2018

We establish a connection between trend filtering and system identification which results in a family of new identification methods for linear, time-varying (LTV) dynamical models based on convex optimization.