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09/01/2023
NeuroSurgeon: A Toolkit for Subnetwork Analysis
Despite recent advances in the field of explainability, much remains unk...
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07/18/2023
Gradient strikes back: How filtering out high frequencies improves explanations
Recent years have witnessed an explosion in the development of novel pre...
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06/20/2023
Computing a human-like reaction time metric from stable recurrent vision models
The meteoric rise in the adoption of deep neural networks as computation...
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06/11/2023
Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization
Feature visualization has gained substantial popularity, particularly af...
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06/11/2023
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation
In recent years, concept-based approaches have emerged as some of the mo...
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06/06/2023
Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex
One of the most impactful findings in computational neuroscience over th...
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06/05/2023
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception
Deep neural networks (DNNs) are known to have a fundamental sensitivity ...
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02/01/2023
Learning Functional Transduction
Research in Machine Learning has polarized into two general regression a...
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01/27/2023
Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines?
An important milestone for AI is the development of algorithms that can ...
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01/26/2023
Break It Down: Evidence for Structural Compositionality in Neural Networks
Many tasks can be described as compositions over subroutines. Though mod...
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11/17/2022
CRAFT: Concept Recursive Activation FacTorization for Explainability
Attribution methods are a popular class of explainability methods that u...
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11/08/2022
Harmonizing the object recognition strategies of deep neural networks with humans
The many successes of deep neural networks (DNNs) over the past decade h...
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08/17/2022
Conviformers: Convolutionally guided Vision Transformer
Vision transformers are nowadays the de-facto preference for image class...
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06/11/2022
A Benchmark for Compositional Visual Reasoning
A fundamental component of human vision is our ability to parse complex ...
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06/10/2022
GAMR: A Guided Attention Model for (visual) Reasoning
Humans continue to outperform modern AI systems in their ability to flex...
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06/09/2022
Xplique: A Deep Learning Explainability Toolbox
Today's most advanced machine-learning models are hardly scrutable. The ...
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05/20/2022
Diversity vs. Recognizability: Human-like generalization in one-shot generative models
Robust generalization to new concepts has long remained a distinctive fe...
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02/15/2022
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis
A variety of methods have been proposed to try to explain how deep neura...
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02/04/2022
A Discourse on MetODS: Meta-Optimized Dynamical Synapses for Meta-Reinforcement Learning
Recent meta-reinforcement learning work has emphasized the importance of...
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12/06/2021
What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods
A multitude of explainability methods and theoretical evaluation scores ...
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11/07/2021
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis
We describe a novel attribution method which is grounded in Sensitivity ...
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09/30/2021
The Challenge of Appearance-Free Object Tracking with Feedforward Neural Networks
Nearly all models for object tracking with artificial neural networks de...
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08/08/2021
Understanding the computational demands underlying visual reasoning
Visual understanding requires comprehending complex visual relations bet...
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05/27/2021
Tracking Without Re-recognition in Humans and Machines
Imagine trying to track one particular fruitfly in a swarm of hundreds. ...
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05/06/2021
KuraNet: Systems of Coupled Oscillators that Learn to Synchronize
Networks of coupled oscillators are some of the most studied objects in ...
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12/01/2020
Iterative VAE as a predictive brain model for out-of-distribution generalization
Our ability to generalize beyond training data to novel, out-of-distribu...
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10/29/2020
Recurrent neural circuits for contour detection
We introduce a deep recurrent neural network architecture that approxima...
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06/16/2020
Neural Optimal Control for Representation Learning
The intriguing connections recently established between neural networks ...
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05/22/2020
Stable and expressive recurrent vision models
Primate vision depends on recurrent processing for reliable perception (...
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06/04/2019
Disentangling neural mechanisms for perceptual grouping
Forming perceptual groups and individuating objects in visual scenes is ...
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11/28/2018
Robust neural circuit reconstruction from serial electron microscopy with convolutional recurrent networks
Recent successes in deep learning have started to impact neuroscience. O...
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06/28/2018
Robust pose tracking with a joint model of appearance and shape
We present a novel approach for estimating the 2D pose of an articulated...
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05/22/2018
Global-and-local attention networks for visual recognition
State-of-the-art deep convolutional networks (DCNs) such as squeeze-and-...
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05/21/2018
Learning long-range spatial dependencies with horizontal gated-recurrent units
Progress in deep learning has spawned great successes in many engineerin...
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02/09/2018
Not-So-CLEVR: Visual Relations Strain Feedforward Neural Networks
The robust and efficient recognition of visual relations in images is a ...
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01/10/2017
What are the visual features underlying human versus machine vision?
Although Deep Convolutional Networks (DCNs) are approaching the accuracy...
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06/03/2016
How Deep is the Feature Analysis underlying Rapid Visual Categorization?
Rapid categorization paradigms have a long history in experimental psych...
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09/07/2015
An end-to-end generative framework for video segmentation and recognition
We describe an end-to-end generative approach for the segmentation and r...
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12/20/2013
