17 citations · 39 across the 10 of their papers we have counts for
11 papers
Recurrent network dynamics explain the time course of perceptual grouping in natural scenes
Sami Mollard, Alekh K. Ashok, Lore Goetschalckx +4
How the brain groups image elements into coherent objects in natural scenes remains unclear. Existing models for grouping in biological vision rely on simplified stimuli with expli…
Better artificial intelligence does not mean better models of biology
Drew Linsley, Pinyuan Feng, Thomas Serre
Deep neural networks (DNNs) once showed increasing alignment with primate perception and neural responses as they improved on vision benchmarks, raising hopes that advances in AI w…
Tracking objects that change in appearance with phase synchrony
Sabine Muzellec, Drew Linsley, Alekh K. Ashok +4
Objects we encounter often change appearance as we interact with them. Changes in illumination (shadows), object pose, or the movement of non-rigid objects can drastically alter av…
The 3D-PC: a benchmark for visual perspective taking in humans and machines
Drew Linsley, Peisen Zhou, Alekh Karkada Ashok +5
Visual perspective taking (VPT) is the ability to perceive and reason about the perspectives of others. It is an essential feature of human intelligence, which develops over the fi…
Neural scaling laws for phenotypic drug discovery
Drew Linsley, John Griffin, Jason Parker Brown +5
Recent breakthroughs by deep neural networks (DNNs) in natural language processing (NLP) and computer vision have been driven by a scale-up of models and data rather than the disco…
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception
Drew Linsley, Pinyuan Feng, Thibaut Boissin +4
Deep neural networks (DNNs) are known to have a fundamental sensitivity to adversarial attacks, perturbations of the input that are imperceptible to humans yet powerful enough to c…
Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization
Thomas Fel, Thibaut Boissin, Victor Boutin +9
Feature visualization has gained substantial popularity, particularly after the influential work by Olah et al. in 2017, which established it as a crucial tool for explainability.…
Harmonizing the object recognition strategies of deep neural networks with humans
Thomas Fel, Ivan Felipe, Drew Linsley +1
The many successes of deep neural networks (DNNs) over the past decade have largely been driven by computational scale rather than insights from biological intelligence. Here, we e…
Recurrent neural circuits for contour detection
Drew Linsley, Junkyung Kim, Alekh Ashok +1
We introduce a deep recurrent neural network architecture that approximates visual cortical circuits. We show that this architecture, which we refer to as the gamma-net, learns to…
Stable and expressive recurrent vision models
Drew Linsley, Alekh Karkada Ashok, Lakshmi Narasimhan Govindarajan +2
Primate vision depends on recurrent processing for reliable perception. A growing body of literature also suggests that recurrent connections improve the learning efficiency and ge…
Learning long-range spatial dependencies with horizontal gated-recurrent units
Drew Linsley, Junkyung Kim, Vijay Veerabadran +1
Progress in deep learning has spawned great successes in many engineering applications. As a prime example, convolutional neural networks, a type of feedforward neural networks, ar…