activity
20162020
most citedAnalytical classical density functionals from an equation learning network

43 citations · 68 across the 3 of their papers we have counts for

collaborators

6 papers

cs.LG202025 cited

Sample-efficient Cross-Entropy Method for Real-time Planning

Cristina Pinneri, Shambhuraj Sawant, Sebastian Blaes +4

Trajectory optimizers for model-based reinforcement learning, such as the Cross-Entropy Method (CEM), can yield compelling results even in high-dimensional control tasks and sparse…

math.OC2019

Fast Non-Parametric Learning to Accelerate Mixed-Integer Programming for Online Hybrid Model Predictive Control

Jia-Jie Zhu, Georg Martius

Today's fast linear algebra and numerical optimization tools have pushed the frontier of model predictive control (MPC) forward, to the efficient control of highly nonlinear and hy…

cond-mat.soft201943 cited

Analytical classical density functionals from an equation learning network

Shang-Chun Lin, Georg Martius, Martin Oettel

We explore the feasibility of using machine learning methods to obtain an analytic form of the classical free energy functional for two model fluids, hard rods and Lennard--Jones,…

cs.RO2019

Robust Affordable 3D Haptic Sensation via Learning Deformation Patterns

Huanbo Sun, Goerg Martius

Haptic sensation is an important modality for interacting with the real world. This paper proposes a general framework of inferring haptic forces on the surface of a 3D structure f…

cs.LG2018

Variational Autoencoders Pursue PCA Directions (by Accident)

Michal Rolinek, Dominik Zietlow, Georg Martius

The Variational Autoencoder (VAE) is a powerful architecture capable of representation learning and generative modeling. When it comes to learning interpretable (disentangled) repr…

q-bio.NC2016

Nonlinear decoding of a complex movie from the mammalian retina

Vicente Botella-Soler, Stéphane Deny, Olivier Marre +1

Retinal circuitry transforms spatiotemporal patterns of light into spiking activity of ganglion cells, which provide the sole visual input to the brain. Recent advances have led to…