J. Kubilius

发表

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

Jonas Kubilius, Mitra J. Z. Hartmann, Chengxu Zhuang, 2017, NIPS.

Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior

Jonas Kubilius, James J DiCarlo, Elias B. Issa, 2019, Nature Neuroscience.

Deep Neural Networks as a Computational Model for Human Shape Sensitivity

H. P. Op de Beeck, Stefania Bracci, J. Kubilius, 2016 .

Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark pdf

Patrick MacAlpine, Matthew J. Hausknecht, Jonas Kubilius, 2021, NeurIPS.

Brain-decoding fMRI reveals how wholes relate to the sum of parts

J. Wagemans, H. O. D. Beeck, J. Kubilius, 2015, Cortex.

The Emergence of Orthographic Word Representations in the Brain: Evaluating a Neural Shape-Based Framework Using fMRI and the HMAX Model

J. Wagemans, H. O. D. Beeck, J. Kubilius, 2012 .

Bistable Gestalts reduce activity in the whole of V1, not just the retinotopically predicted parts.

Johan Wagemans, Jonas Kubilius, Hans P Op de Beeck, 2012, Journal of vision.

Cue-invariant shape recognition in rats as tested with second-order contours.

H. P. Op de Beeck, J. Kubilius, Christophe Bossens, 2015, Journal of vision.

Sensitivity to Nonaccidental Configurations of Two-Line Stimuli

J. Wagemans, J. Kubilius, C. Sleurs, 2017, i-Perception.

Integrative Benchmarking to Advance Neurally Mechanistic Models of Human Intelligence

Jonas Kubilius, Martin Schrimpf, James J. DiCarlo, 2020, Neuron.

Mirror-Image Sensitivity and Invariance in Object and Scene Processing Pathways

Daniel D. Dilks, Nancy Kanwisher, Jonas Kubilius, 2011, The Journal of Neuroscience.

Emergence of Perceptual Gestalts in the Human Visual Cortex

Johan Wagemans, Jonas Kubilius, Hans Op de Beeck, 2011, Psychological science.

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation

Josh H. McDermott, Daniel L. K. Yamins, Julian De Freitas, 2020, NeurIPS Datasets and Benchmarks.

A conceptual framework of computations in mid-level vision

Johan Wagemans, Jonas Kubilius, Hans P. Op de Beeck, 2014, Front. Comput. Neurosci..

A framework for streamlining research workflow in neuroscience and psychology

Jonas Kubilius, J. Kubilius, 2014, Front. Neuroinform..

Recurrent Connections in the Primate Ventral Visual Stream Mediate a Tradeoff Between Task Performance and Network Size During Core Object Recognition

Daniel L. K. Yamins, J. DiCarlo, David Sussillo, 2022, bioRxiv.

Deep Neural Networks as a Computational Model for Human Shape Sensitivity

Jonas Kubilius, Stefania Bracci, Hans P. Op de Beeck, 2016, PLoS Comput. Biol..

Encoding of configural regularity in the human visual system.

Johan Wagemans, Jonas Kubilius, Hans P Op de Beeck, 2014, Journal of vision.

Configural Gestalts remain nothing more than the sum of their parts in visual agnosia

Johan Wagemans, Jonas Kubilius, Hans P. Op de Beeck, 2013, i-Perception.

Emergence of Perceptual Gestalts in the Human Visual Cortex

Johan Wagemans, Jonas Kubilius, Hans P Op de Beeck, 2011, Psychological science.

Integrative Benchmarking to Advance Neurally Mechanistic Models of Human Intelligence

Jonas Kubilius, Martin Schrimpf, James J. DiCarlo, 2020, Neuron.

The occipital place area represents the local elements of scenes

Daniel D. Dilks, Nancy Kanwisher, Jonas Kubilius, 2016, NeuroImage.

Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?

Jonas Kubilius, Martin Schrimpf, Ha Hong, 2018, bioRxiv.

CORnet: Modeling the Neural Mechanisms of Core Object Recognition

Aran Nayebi, Jonas Kubilius, Martin Schrimpf, 2018, bioRxiv.

Goal-Driven Recurrent Neural Network Models of the Ventral Visual Stream

Daniel L. K. Yamins, J. DiCarlo, David Sussillo, 2021 .

Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior

Elias B. Issa, J. DiCarlo, Kohitij Kar, 2018, Nature Neuroscience.

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

Elias B. Issa, Daniel L. K. Yamins, J. DiCarlo, 2019, NeurIPS.

Recurrent Connections in the Primate Ventral Visual Stream Mediate a Tradeoff Between Task Performance and Network Size During Core Object Recognition

Daniel L. K. Yamins, J. DiCarlo, David Sussillo, 2021, bioRxiv.

Task-Driven Convolutional Recurrent Models of the Visual System

Surya Ganguli, Aran Nayebi, Jonas Kubilius, 2018, NeurIPS.

REAL ROOTS !

J. Kubilius, 2002 .

Can Deep Neural Networks Rival Human Ability to Generalize in Core Object Recognition

Jonas Kubilius, James J. DiCarlo, Kohitij Kar, 2018 .

CORnet: Modeling the Neural Mechanisms of Core Object Recognition

J. DiCarlo, Daniel Yamins, Aran Nayebi, 2018, bioRxiv.

Predict, then simplify

Jonas Kubilius, J. Kubilius, 2017, NeuroImage.

Probabilistic Methods in the Theory of Numbers

J. Kubilius, J. Kubilius, 1964 .

Some highlights from the history of probabilistic number theory

A. Rényi, J. Littlewood, A. Kolmogorov, 2007 .

Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior

James J. DiCarlo, Elias B. Issa, Kubilius Jonas, 2018, Nature Neuroscience.

Estimating the second central moment for any additive arithmetic functions

J. Kubilius, 1983 .

Mirror-Image Sensitivity and Invariance in Object and Scene Processing Pathways

Daniel D. Dilks, E. Spelke, N. Kanwisher, 2011, The Journal of Neuroscience.

From What Scale of Representation Does Multivariate Pattern Analysis Decode Information?

Jonas Kubilius, Annelies Baeck, J. Kubilius, 2010, The Journal of Neuroscience.

Sensitivity to Nonaccidental Configurations of Two-Line Stimuli

J. Wagemans, J. Kubilius, C. Sleurs, 2017, i-Perception.

Additive arithmetic functions and Brownian motion

J. Kubilius, 1976 .