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Workshop

Shared Visual Representations in Human and Machine Intelligence (SVRHM)

Arturo Deza ⋅ Joshua Peterson ⋅ N Apurva Ratan Murty ⋅ Tom Griffiths
Project Page [ Contact: svrhm2022@gmail.com ]

Video

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Schedule

Timezone: America/Los_Angeles
6:45 AM
Welcome + Opening Remarks
N Apurva Ratan Murty
7:10 AM
Learning to Look by Self-Prediction
Matthew Grimes
8:40 AM
Kate Storrs
11:00 AM
Line Drawings as Communication
Phillip Isola
11:20 AM
Tangible Abstractions
Tom White
3:30 PM
What's the endgame of neuroAI?
Patrick Mineault
Exploring the perceptual straightness of adversarially robust and biologically-inspired visual representations
Anne Harrington ⋅ Vasha DuTell ⋅ Ayush Tewari ⋅ Mark Hamilton ⋅ Simon Stent ⋅ Ruth Rosenholtz ⋅ Bill Freeman
The emergence of visual simulation in task-optimized recurrent neural networks
Alekh Karkada Ashok ⋅ Lakshmi Narasimhan Govindarajan ⋅ Drew Linsley ⋅ David Sheinberg ⋅ Thomas Serre
Predictive Dynamics Improve Noise Robustness in a Deep Network Model of the Human Auditory System
Ching Fang ⋅ Erica Shook ⋅ Justin Buck ⋅ Guillermo Horga
Implementing Divisive Normalization in CNNs Improves Robustness to Common Image Corruptions
Andrew Cirincione ⋅ Reginald Verrier ⋅ Artiom Bic ⋅ Stephanie Olaiya ⋅ James J DiCarlo ⋅ Lawrence Udeigwe ⋅ Tiago Marques
Fast temporal decoding from large-scale neural recordings in monkey visual cortex
Jerome Hadorn ⋅ Zuowen Wang ⋅ Bodo Rueckauer ⋅ Xing Chen ⋅ Pieter Roelfsema ⋅ Shih-Chii Liu
How do humans and machine learning models track multiple objects through occlusion?
Benjamin Peters ⋅ Eivinas Butkus ⋅ Nikolaus Kriegeskorte
Workshop version: How hard are computer vision datasets? Calibrating dataset difficulty to viewing time
David Mayo ⋅ Jesse Cummings ⋅ Xinyu Lin ⋅ Dan Gutfreund ⋅ Boris Katz ⋅ Andrei Barbu
Redundancy and dependency in brain activities
Sikun Lin ⋅ Thomas Sprague ⋅ Ambuj K Singh
Generalized Predictive Coding: Bayesian Inference in Static and Dynamic models
André Ofner ⋅ Beren Millidge ⋅ Sebastian Stober
Primate Inferotemporal Cortex Neurons Generalize Better to Novel Image Distributions Than Analogous Deep Neural Networks Units
Marliawaty I Gusti Bagus ⋅ Tiago Marques ⋅ Sachi Sanghavi ⋅ James J DiCarlo ⋅ Martin Schrimpf
Teacher-generated pseudo human spatial-attention labels boost contrastive learning models
Yushi Yao ⋅ Chang Ye ⋅ Junfeng He ⋅ Gamaleldin Elsayed
Model Stitching: Looking For Functional Similarity Between Representations
Adriano Hernandez ⋅ Rumen Dangovski ⋅ Peter Y. Lu
Topographic DCNNs trained on a single self-supervised task capture the functional organization of cortex into visual processing streams
Dawn Finzi ⋅ Eshed Margalit ⋅ Kendrick Kay ⋅ Dan Yamins ⋅ Kalanit Grill-Spector
Volumetric Neural Human for Robust Pose Optimization via Analysis-by-synthesis
Pengliang Ji ⋅ Angtian Wang ⋅ Yi Zhang ⋅ Adam Kortylewski ⋅ Alan Yuille
What does an Adversarial Color look like?
John Chin ⋅ Arturo Deza
Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement
Michael Chang ⋅ Alyssa L Dayan ⋅ Franziska Meier ⋅ Tom Griffiths ⋅ Sergey Levine ⋅ Amy Zhang
Top-down effects in an early visual cortex inspired hierarchical Variational Autoencoder
Ferenc Csikor ⋅ Balázs Meszéna ⋅ Bence Szabó ⋅ Gergo Orban
Human alignment of neural network representations
Lukas Muttenthaler ⋅ Lorenz Linhardt ⋅ Jonas Dippel ⋅ Robert Vandermeulen ⋅ Simon Kornblith
Learning to Look by Self-Prediction
Matthew Grimes ⋅ Joseph Modayil ⋅ Piotr Mirowski ⋅ Dushyant Rao ⋅ Raia Hadsell
Enforcing Object Permanence using Hierarchical Object-Centric Generative Models
Toon Van de Maele ⋅ Stefano Ferraro ⋅ Tim Verbelen ⋅ Bart Dhoedt
Adding neuroplasticity to a CNN-based in-silico model of neurodegeneration
Jasmine Moore ⋅ Matthias Wilms ⋅ Kayson Fakhar ⋅ Fatemeh Hadaeghi ⋅ Claus Hilgetag ⋅ Nils Daniel Forkert