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Jonas Kubilius

4 accepted papers

2021

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation

NeurIPS 2021poster

We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation. TDW enables the simulation of high-fidelity sensory data and physical interactions between mobile agents and objects in rich 3D environments. Unique properties include real-time near-photo-realistic image ren…

Cited by 342SourcecodeScholar
2019

Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs

NeurIPS 2019oral

Deep convolutional artificial neural networks (ANNs) are the leading class of candidate models of the mechanisms of visual processing in the primate ventral stream. While initially inspired by brain anatomy, over the past years, these ANNs have evolved from a simple eight-layer architecture in AlexN…

2018

Task-Driven Convolutional Recurrent Models of the Visual System

NeurIPS 2018poster

Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object classification tasks such as ImageNet. Further, they are quantitatively accurate models of temporally-averaged responses of neurons in the primate brain's visual system. However, biological visual systems ha…

2017

Toward Goal-Driven Neural Network Models for the Rodent Whisker-Trigeminal System

NeurIPS 2017oral

In large part, rodents “see” the world through their whiskers, a powerful tactile sense enabled by a series of brain areas that form the whisker-trigeminal system. Raw sensory data arrives in the form of mechanical input to the exquisitely sensitive, actively-controllable whisker array, and is proce…