Home /

Research

Showing 535 - 540 / 904

Few-shot Object Grounding and Mapping for Natural Language Robot Instruction Following


Authors:  ValtsBlukis, RossA.Knepper, YoavArtzi....
Published date-11/14/2020
Tasks:  ContinuousControl

Abstract: We study the problem of learning a robot policy to follow natural language instructions that can be easily extended to reason about new objects. We introduce a few-shot language-conditioned object …

Self Normalizing Flows


Authors:  T.AndersonKeller, JornW.T.Peters, PriyankJaini....
Published date-11/14/2020

Abstract: Efficient gradient computation of the Jacobian determinant term is a core problem of the normalizing flow framework. Thus, most proposed flow models either restrict to a function class with easy …

Discovery of the Hidden State in Ionic Models Using a Domain-Specific Recurrent Neural Network


Authors:  ShahriarIravanian....
Published date-11/14/2020

Abstract: Ionic models, the set of ordinary differential equations (ODEs) describing the time evolution of the state of excitable cells, are the cornerstone of modeling in neuro- and cardiac electrophysiology. Modern …

Deep Spatial Learning with Molecular Vibration


Authors:  ZiyangZhang, YingtaoLuo....
Published date-11/14/2020

Abstract: Machine learning over-fitting caused by data scarcity greatly limits the application of machine learning for molecules. Due to manufacturing processes difference, big data is not always rendered available through computational …

Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery


Authors:  IssamLaradji, PauRodriguez, FreddieKalaitzis....
Published date-11/14/2020

Abstract: Cattle farming is responsible for 8.8\% of greenhouse gas emissions worldwide. In addition to the methane emitted due to their digestive process, the growing need for grazing areas is an …

Factorized Gaussian Process Variational Autoencoders


Authors:  MetodJazbec, MichaelPearce, VincentFortuin....
Published date-11/14/2020

Abstract: Variational autoencoders often assume isotropic Gaussian priors and mean-field posteriors, hence do not exploit structure in scenarios where we may expect similarity or consistency across latent variables. Gaussian process variational …

Filter by

Categories

Tags