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Thomas Hannagan
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2020 – today
- 2024
- [c6]Yixiao Wang, Chen Tang, Lingfeng Sun, Simone Rossi, Yichen Xie, Chensheng Peng, Thomas Hannagan, Stefano Sabatini, Nicola Poerio, Masayoshi Tomizuka, Wei Zhan:
Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation. ECCV (29) 2024: 324-341 - [i6]Yixiao Wang, Chen Tang, Lingfeng Sun, Simone Rossi, Yichen Xie, Chensheng Peng, Thomas Hannagan, Stefano Sabatini, Nicola Poerio, Masayoshi Tomizuka, Wei Zhan:
Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation. CoRR abs/2408.00766 (2024) - 2023
- [c5]Simone Rossi, Ankit Singh, Thomas Hannagan:
On permutation symmetries in Bayesian neural network posteriors: a variational perspective. NeurIPS 2023 - [i5]Simone Rossi, Ankit Singh, Thomas Hannagan:
On permutation symmetries in Bayesian neural network posteriors: a variational perspective. CoRR abs/2310.10171 (2023) - [i4]Marc Schachtsiek, Simone Rossi, Thomas Hannagan:
Class Balanced Dynamic Acquisition for Domain Adaptive Semantic Segmentation using Active Learning. CoRR abs/2311.14146 (2023) - 2022
- [j7]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, Thomas Hannagan, David Bertrand:
Rethinking Weight Decay for Efficient Neural Network Pruning. J. Imaging 8(3): 64 (2022) - [c4]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, David Bertrand, Thomas Hannagan:
Leveraging Structured Pruning of Convolutional Neural Networks. SiPS 2022: 1-6 - [c3]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, David Bertrand, Thomas Hannagan:
Energy Consumption Analysis of Pruned Semantic Segmentation Networks on an Embedded GPU. SYSINT 2022: 553-563 - [i3]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, David Bertrand, Thomas Hannagan:
Leveraging Structured Pruning of Convolutional Neural Networks. CoRR abs/2206.06247 (2022) - [i2]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, David Bertrand, Thomas Hannagan:
Energy Consumption Analysis of pruned Semantic Segmentation Networks on an Embedded GPU. CoRR abs/2206.06255 (2022) - 2020
- [i1]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, Thomas Hannagan, David Bertrand:
Continuous Pruning of Deep Convolutional Networks Using Selective Weight Decay. CoRR abs/2011.10520 (2020)
2010 – 2019
- 2013
- [j6]Frédéric Dandurand, Thomas Hannagan, Jonathan Grainger:
Computational models of location-invariant orthographic processing. Connect. Sci. 25(1): 1-26 (2013) - [j5]Jasmin Léveillé, Thomas Hannagan:
Learning Spatial Invariance with the Trace Rule in Nonuniform Distributions. Neural Comput. 25(5): 1261-1276 (2013) - [j4]Thomas Hannagan, Jonathan Grainger:
The Lazy Visual Word Form Area: Computational Insights into Location-Sensitivity. PLoS Comput. Biol. 9(10) (2013) - 2012
- [j3]Thomas Hannagan, Jonathan Grainger:
Protein Analysis Meets Visual Word Recognition: A Case for String Kernels in the Brain. Cogn. Sci. 36(4): 575-606 (2012) - [c2]Thomas Hannagan, James Magnusson, Jonathan Grainger:
A time-invariant connectionist model of spoken word recognition. CogSci 2012 - 2011
- [j2]Thomas Hannagan, Emmanuel Dupoux, Anne Christophe:
Holographic String Encoding. Cogn. Sci. 35(1): 79-118 (2011) - [j1]Thomas Hannagan, Frédéric Dandurand, Jonathan Grainger:
Broken Symmetries in a Location-Invariant Word Recognition Network. Neural Comput. 23(1): 251-283 (2011) - [c1]Thomas Hannagan, Rachel Wu:
Cued multimodal learning in infancy: a neuro-computational model. CogSci 2011
Coauthor Index
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