Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images. - Bernd Heisele; Thomas Serre; Sayan Mukherjee 001; Tomaso A. Poggio (CVPR (2), 2001)

Component-based Face Detection. - Bernd Heisele; Thomas Serre; Massimiliano Pontil; Tomaso A. Poggio (CVPR (1), 2001)

Categorization by Learning and Combining Object Parts. - Bernd Heisele; Thomas Serre; Massimiliano Pontil; Thomas Vetter; Tomaso A. Poggio (NIPS, 2001)

On the Role of Object-Specific Features for Real World Object Recognition in Biological Vision. - Thomas Serre; Maximilian Riesenhuber; Jennifer Louie; Tomaso A. Poggio (Biologically Motivated Computer Vision, 2002)

Hierarchical classification and feature reduction for fast face detection with support vector machines. - Bernd Heisele; Thomas Serre; Sam Prentice; Tomaso A. Poggio (Pattern Recognit., 2003)

Using Component Features for Face Recognition. - Yuri Ivanov; Bernd Heisele; Thomas Serre (FGR, 2004)

Object Recognition with Features Inspired by Visual Cortex. - Thomas Serre; Lior Wolf; Tomaso A. Poggio (CVPR (2), 2005)

Learning Features of Intermediate Complexity for the Recognition of Biological Motion. - Rodrigo Sigala; Thomas Serre; Tomaso A. Poggio; Martin A. Giese (ICANN (1), 2005)

A Biologically Inspired System for Action Recognition. - Hueihan Jhuang; Thomas Serre; Lior Wolf; Tomaso A. Poggio (ICCV, 2007)

A Component-based Framework for Face Detection and Identification. - Bernd Heisele; Thomas Serre; Tomaso A. Poggio (Int. J. Comput. Vis., 2007)

Robust Object Recognition with Cortex-Like Mechanisms. - Thomas Serre; Lior Wolf; Stanley M. Bileschi; Maximilian Riesenhuber; Tomaso A. Poggio (IEEE Trans. Pattern Anal. Mach. Intell., 2007)

The story of a single cell: Peeking into the semantics of spikes. - Roi Kliper; Thomas Serre; Daphna Weinshall; Israel Nelken (CIP, 2010)

Trainable, vision-based automated home cage behavioral phenotyping. - Hueihan Jhuang; Estíbaliz Garrote; Nicholas Edelman; Tomaso A. Poggio; Andrew Steele; Thomas Serre (MB, 2010)

A neuromorphic approach to computer vision. - Thomas Serre; Tomaso A. Poggio (Commun. ACM, 2010)

Reading the mind's eye: Decoding category information during mental imagery. - Leila Reddy; Naotsugu Tsuchiya; Thomas Serre (NeuroImage, 2010)

Attention as a Bayesian inference process. - Sharat Chikkerur; Thomas Serre; Cheston Tan; Tomaso A. Poggio (Human Vision and Electronic Imaging, 2011)

HMDB: A large video database for human motion recognition. - Hildegard Kuehne; Hueihan Jhuang; Estíbaliz Garrote; Tomaso A. Poggio; Thomas Serre (ICCV, 2011)

The Neural Dynamics of Visual Processing in Monkey Extrastriate Cortex: A Comparison between Univariate and Multivariate Techniques. - Maxime Cauchoix; Ali Bilgin Arslan; Denis Fize; Thomas Serre (MLINI, 2011)

A New Biologically Inspired Color Image Descriptor. - Jun Zhang 017; Youssef Barhomi; Thomas Serre (ECCV (5), 2012)

Neural representation of action sequences: how far can a simple snippet-matching model take us? - Cheston Tan; Jedediah M. Singer; Thomas Serre; David L. Sheinberg; Tomaso A. Poggio (NIPS, 2013)

Models of visual cortex. - Tomaso A. Poggio; Thomas Serre (Scholarpedia, 2013)

The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities. - Hilde Kuehne; Ali Bilgin Arslan; Thomas Serre (CVPR, 2014)

Learning Sparse Prototypes for Crowd Perception via Ensemble Coding Mechanisms. - Yanhao Zhang 001; Shengping Zhang; Qingming Huang; Thomas Serre (HBU, 2014)

Neuronal Synchrony in Complex-Valued Deep Networks. - David P. Reichert; Thomas Serre (ICLR (Poster), 2014)

Hierarchical Models of the Visual System. - Thomas Serre (Encyclopedia of Computational Neuroscience, 2014)

Cooking in the kitchen: A generative approach to the recognition, parsing and segmentation of human daily activities. - Hilde Kuehne; Thomas Serre (CoRR, 2015)

Towards a generative approach to activity recognition and segmentation. - Hilde Kuehne; Thomas Serre (CoRR, 2015)

Unsupervised invariance learning of transformation sequences in a model of object recognition yields selectivity for non-accidental properties. - Sarah M. Parker; Thomas Serre (Frontiers Comput. Neurosci., 2015)

Explaining the Timing of Natural Scene Understanding with a Computational Model of Perceptual Categorization. - Imri Sofer; Sébastien M. Crouzet; Thomas Serre (PLoS Comput. Biol., 2015)

How Deep is the Feature Analysis underlying Rapid Visual Categorization? - Sven Eberhardt; Jonah G. Cader; Thomas Serre (NIPS, 2016)

An end-to-end generative framework for video segmentation and recognition. - Hilde Kuehne; Juergen Gall; Thomas Serre (WACV, 2016)

Fast ventral stream neural activity enables rapid visual categorization. - Maxime Cauchoix; Sébastien M. Crouzet; Denis Fize; Thomas Serre (NeuroImage, 2016)

Computer vision cracks the leaf code. - Peter Wilf; Shengping Zhang; Sharat Chikkerur; Stefan A. Little; Scott L. Wing; Thomas Serre (Proc. Natl. Acad. Sci. USA, 2016)

What are the Visual Features Underlying Human Versus Machine Vision? - Drew Linsley; Sven Eberhardt; Tarun Sharma; Pankaj Gupta; Thomas Serre (ICCV Workshops, 2017)

Clicktionary: A Web-based Game for Exploring the Atoms of Object Recognition. - Drew Linsley; Sven Eberhardt; Tarun Sharma; Pankaj Gupta; Thomas Serre (CoRR, 2017)

Learning to predict action potentials end-to-end from calcium imaging data. - Drew Linsley; Jeremy W. Linsley; Tarun Sharma; Nathan Meyers; Thomas Serre (CISS, 2018)

Same-different problems strain convolutional neural networks. - Matthew Ricci; Junkyung Kim; Thomas Serre (CogSci, 2018)

Learning long-range spatial dependencies with horizontal gated recurrent units. - Drew Linsley; Junkyung Kim; Vijay Veerabadran; Charles Windolf; Thomas Serre (NeurIPS, 2018)

Not-So-CLEVR: Visual Relations Strain Feedforward Neural Networks. - Matthew Ricci; Junkyung Kim; Thomas Serre (CoRR, 2018)

Learning long-range spatial dependencies with horizontal gated-recurrent units. - Drew Linsley; Junkyung Kim; Vijay Veerabadran; Thomas Serre (CoRR, 2018)

Global-and-local attention networks for visual recognition. - Drew Linsley; Dan Scheibler; Sven Eberhardt; Thomas Serre (CoRR, 2018)

Robust pose tracking with a joint model of appearance and shape. - Yuliang Guo; Lakshmi Narasimhan Govindarajan; Benjamin B. Kimia; Thomas Serre (CoRR, 2018)

Robust neural circuit reconstruction from serial electron microscopy with convolutional recurrent networks. - Drew Linsley; Junkyung Kim; David Berson; Thomas Serre (CoRR, 2018)

Learning what and where to attend. - Drew Linsley; Dan Shiebler; Sven Eberhardt; Thomas Serre (ICLR (Poster), 2019)

Disentangling neural mechanisms for perceptual grouping. - Junkyung Kim; Drew Linsley; Kalpit Thakkar; Thomas Serre (ICLR, 2020)

Recurrent neural circuits for contour detection. - Drew Linsley; Junkyung Kim; Alekh Ashok; Thomas Serre (ICLR, 2020)

Stable and expressive recurrent vision models. - Drew Linsley; Alekh Karkada Ashok; Lakshmi Narasimhan Govindarajan; Rex G. Liu; Thomas Serre (NeurIPS, 2020)

Neural Optimal Control for Representation Learning. - Mathieu Chalvidal; Matthew Ricci; Rufin VanRullen; Thomas Serre (CoRR, 2020)

Iterative VAE as a predictive brain model for out-of-distribution generalization. - Victor Boutin; Aimen Zerroug; Minju Jung; Thomas Serre (CoRR, 2020)

Go with the flow: Adaptive control for Neural ODEs. - Mathieu Chalvidal; Matthew Ricci; Rufin VanRullen; Thomas Serre (ICLR, 2021)

Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis. - Thomas Fel; Rémi Cadène; Mathieu Chalvidal; Matthieu Cord; David Vigouroux; Thomas Serre (NeurIPS, 2021)

Tracking Without Re-recognition in Humans and Machines. - Drew Linsley; Girik Malik; Junkyung Kim; Lakshmi Narasimhan Govindarajan; Ennio Mingolla; Thomas Serre (NeurIPS, 2021)

KuraNet: Systems of Coupled Oscillators that Learn to Synchronize. - Matthew Ricci; Minju Jung; Yuwei Zhang 001; Mathieu Chalvidal; Aneri Soni; Thomas Serre (CoRR, 2021)

The Challenge of Appearance-Free Object Tracking with Feedforward Neural Networks. - Girik Malik; Drew Linsley; Thomas Serre; Ennio Mingolla (CoRR, 2021)

Diversity vs. Recognizability: Human-like generalization in one-shot generative models. - Victor Boutin; Lakshya Singhal; Xavier Thomas; Thomas Serre (NeurIPS, 2022)

Meta-Reinforcement Learning with Self-Modifying Networks. - Mathieu Chalvidal; Thomas Serre; Rufin VanRullen (NeurIPS, 2022)

What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods. - Julien Colin; Thomas Fel; Rémi Cadène; Thomas Serre (NeurIPS, 2022)

Harmonizing the object recognition strategies of deep neural networks with humans. - Thomas Fel; Ivan F. Rodriguez Rodriguez; Drew Linsley; Thomas Serre (NeurIPS, 2022)

A Benchmark for Compositional Visual Reasoning. - Aimen Zerroug; Mohit Vaishnav; Julien Colin; Sebastian Musslick; Thomas Serre (NeurIPS, 2022)

How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural Networks. - Thomas Fel; David Vigouroux; Rémi Cadène; Thomas Serre (WACV, 2022)

How and What to Learn: Taxonomizing Self-Supervised Learning for 3D Action Recognition. - Amor Ben Tanfous; Aimen Zerroug; Drew Linsley; Thomas Serre (WACV, 2022)

A Discourse on MetODS: Meta-Optimized Dynamical Synapses for Meta-Reinforcement Learning. - Mathieu Chalvidal; Thomas Serre; Rufin VanRullen (CoRR, 2022)

Xplique: A Deep Learning Explainability Toolbox. - Thomas Fel; Lucas Hervier; David Vigouroux; Antonin Poché; Justin Plakoo; Rémi Cadène; Mathieu Chalvidal; Julien Colin; Thibaut Boissin; Louis Béthune; Agustin Martin Picard; Claire Nicodeme; et al. (CoRR, 2022)

MAREO: Memory- and Attention- based visual REasOning. - Mohit Vaishnav; Thomas Serre (CoRR, 2022)

Conviformers: Convolutionally guided Vision Transformer. - Mohit Vaishnav; Thomas Fel; Ivan Felipe Rodríguez; Thomas Serre (CoRR, 2022)

Harmonizing the object recognition strategies of deep neural networks with humans. - Thomas Fel; Ivan Felipe Rodríguez; Drew Linsley; Thomas Serre (CoRR, 2022)

Understanding the Computational Demands Underlying Visual Reasoning. - Mohit Vaishnav; Rémi Cadène; Andrea Alamia; Drew Linsley; Rufin VanRullen; Thomas Serre (Neural Comput., 2022)

Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis. - Thomas Fel; Melanie Ducoffe; David Vigouroux; Rémi Cadène; Mikael Capelle; Claire Nicodème; Thomas Serre (CVPR, 2023)

CRAFT: Concept Recursive Activation FacTorization for Explainability. - Thomas Fel; Agustin Martin Picard; Louis Béthune; Thibaut Boissin; David Vigouroux; Julien Colin; Rémi Cadène; Thomas Serre (CVPR, 2023)

GAMR: A Guided Attention Model for (visual) Reasoning. - Mohit Vaishnav; Thomas Serre (ICLR, 2023)

Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines? - Victor Boutin; Thomas Fel; Lakshya Singhal; Rishav Mukherji; Akash Nagaraj; Julien Colin; Thomas Serre (ICML, 2023)

Learning Functional Transduction. - Mathieu Chalvidal; Thomas Serre; Rufin VanRullen (NeurIPS, 2023)

A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation. - Thomas Fel; Victor Boutin; Louis Béthune; Rémi Cadène; Mazda Moayeri; Léo Andéol; Mathieu Chalvidal; Thomas Serre (NeurIPS, 2023)

Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization. - Thomas Fel; Thibaut Boissin; Victor Boutin; Agustin Picard; Paul Novello; Julien Colin; Drew Linsley; Tom Rousseau; Rémi Cadène; Lore Goetschalckx; Laurent Gardes; Thomas Serre (NeurIPS, 2023)

Computing a human-like reaction time metric from stable recurrent vision models. - Lore Goetschalckx; Lakshmi Narasimhan Govindarajan; Alekh Karkada Ashok; Aarit Ahuja; David L. Sheinberg; Thomas Serre (NeurIPS, 2023)

Break It Down: Evidence for Structural Compositionality in Neural Networks. - Michael A. Lepori; Thomas Serre; Ellie Pavlick (NeurIPS, 2023)

Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex. - Drew Linsley; Ivan F. Rodriguez Rodriguez; Thomas Fel; Michael Arcaro; Saloni Sharma; Margaret S. Livingstone; Thomas Serre (NeurIPS, 2023)

Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception. - Drew Linsley; Pinyuan Feng; Thibaut Boissin; Alekh Karkada Ashok; Thomas Fel; Stephanie Olaiya; Thomas Serre (CoRR, 2023)

Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex. - Drew Linsley; Ivan Felipe Rodríguez; Thomas Fel; Michael Arcaro; Saloni Sharma; Margaret S. Livingstone; Thomas Serre (CoRR, 2023)

Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization. - Thomas Fel; Thibaut Boissin; Victor Boutin; Agustin Martin Picard; Paul Novello; Julien Colin; Drew Linsley; Tom Rousseau; Rémi Cadène; Laurent Gardes; Thomas Serre (CoRR, 2023)

Gradient strikes back: How filtering out high frequencies improves explanations. - Sabine Muzellec; Léo Andéol; Thomas Fel; Rufin VanRullen; Thomas Serre (CoRR, 2023)

NeuroSurgeon: A Toolkit for Subnetwork Analysis. - Michael A. Lepori; Ellie Pavlick; Thomas Serre (CoRR, 2023)

Diagnosing and exploiting the computational demands of videos games for deep reinforcement learning. - Lakshmi Narasimhan Govindarajan; Rex G. Liu; Drew Linsley; Alekh Karkada Ashok; Max Reuter; Michael J. Frank; Thomas Serre (CoRR, 2023)

Uncovering Intermediate Variables in Transformers using Circuit Probing. - Michael A. Lepori; Thomas Serre; Ellie Pavlick (CoRR, 2023)

Categorizing the Visual Environment and Analyzing the Visual Attention of Dogs. - Shreyas Sundara Raman; Madeline H. Pelgrim; Daphna Buchsbaum; Thomas Serre (CoRR, 2023)

Fixing the problems of deep neural networks will require better training data and learning algorithms. - Drew Linsley; Thomas Serre (CoRR, 2023)

A Lightweight Dual-Stage Framework for Personalized Speech Enhancement Based on Deepfilternet2. - Thomas Serre; Mathieu Fontaine 002; Éric Benhaim; Geoffroy Dutour; Slim Essid (ICASSP Workshops, 2024)

Saliency strikes back: How filtering out high frequencies improves white-box explanations. - Sabine Muzellec; Thomas Fel; Victor Boutin; Léo Andéol; Rufin VanRullen; Thomas Serre (ICML, 2024)

Latent Representation Matters: Human-like Sketches in One-shot Drawing Tasks. - Victor Boutin; Rishav Mukherji; Aditya Agrawal; Sabine Muzellec; Thomas Fel; Thomas Serre; Rufin VanRullen (NeurIPS, 2024)

RTify: Aligning Deep Neural Networks with Human Behavioral Decisions. - Yu-Ang Cheng; Ivan F. Rodriguez Rodriguez; Sixuan Chen; Kohitij Kar; Takeo Watanabe; Thomas Serre (NeurIPS, 2024)

Understanding Visual Feature Reliance through the Lens of Complexity. - Thomas Fel; Louis Béthune; Andrew K. Lampinen; Thomas Serre; Katherine L. Hermann (NeurIPS, 2024)

Beyond the Doors of Perception: Vision Transformers Represent Relations Between Objects. - Michael A. Lepori; Alexa R. Tartaglini; Wai Keen Vong; Thomas Serre; Brenden M. Lake; Ellie Pavlick (NeurIPS, 2024)

RTify: Aligning Deep Neural Networks with Human Behavioral Decisions. - Yu-Ang Cheng; Ivan Felipe Rodríguez; Sixuan Chen; Kohitij Kar; Takeo Watanabe; Thomas Serre (CoRR, 2024)

Local vs distributed representations: What is the right basis for interpretability? - Julien Colin; Lore Goetschalckx; Thomas Fel; Victor Boutin; Jay Gopal; Thomas Serre; Nuria Oliver (CoRR, 2024)

Contrastive Knowledge Distillation for Embedding Refinement in Personalized Speech Enhancement. - Thomas Serre; Mathieu Fontaine 002; Éric Benhaim; Slim Essid (ICASSP, 2025)

The 3D-PC: a benchmark for visual perspective taking in humans and machines. - Drew Linsley; Peisen Zhou; Alekh Karkada Ashok; Akash Nagaraj; Gaurav Gaonkar; Francis E. Lewis; Zygmunt Pizlo; Thomas Serre (ICLR, 2025)

Tracking objects that change in appearance with phase synchrony. - Sabine Muzellec; Drew Linsley; Alekh Karkada Ashok; Ennio Mingolla; Girik Malik; Rufin VanRullen; Thomas Serre (ICLR, 2025)

Evaluating Dogs' Real-World Visual Environment and Attention. - Madeline H. Pelgrim; Shreyas Sundara Raman; Thomas Serre; Daphna Buchsbaum (Cogn. Sci., 2025)

Enhancing deep neural networks through complex-valued representations and Kuramoto synchronization dynamics. - Sabine Muzellec; Andrea Alamia; Thomas Serre; Rufin VanRullen (Trans. Mach. Learn. Res., 2025)

Better artificial intelligence does not mean better models of biology. - Drew Linsley; Pinyuan Feng; Thomas Serre (CoRR, 2025)

Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models. - Louis Béthune; David Vigouroux; Yilun Du; Rufin VanRullen; Thomas Serre; Victor Boutin (CoRR, 2025)

Is This Just Fantasy? Language Model Representations Reflect Human Judgments of Event Plausibility. - Michael A. Lepori; Jennifer Hu 001; Ishita Dasgupta 001; Roma Patel; Thomas Serre; Ellie Pavlick (CoRR, 2025)

GASPnet: Global Agreement to Synchronize Phases. - Andrea Alamia; Sabine Muzellec; Thomas Serre; Rufin VanRullen (CoRR, 2025)