Thijs Vogels

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 21

Top Topics

Heterogeneous Data

Top Venues

ACM Trans. Graph.

Publications

Daniel Morales-Brotons, Thijs Vogels, Hadrien Hendrikx
Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits. Trans. Mach. Learn. Res. 2024 (2024)
Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
Beyond spectral gap (extended): The role of the topology in decentralized learning. CoRR (2023)
Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels, Martin Jaggi, Tanja Käser, Mary-Anne Hartley
MultiMoDN - Multimodal, Multi-Task, Interpretable Modular Networks. NeurIPS (2023)
Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim, Michael C. Gastpar
LASER: Linear Compression in Wireless Distributed Optimization. CoRR (2023)
Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels, Martin Jaggi, Tanja Käser, Mary-Anne Hartley
MultiModN- Multimodal, Multi-Task, Interpretable Modular Networks. CoRR (2023)
Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
Beyond spectral gap: The role of the topology in decentralized learning. CoRR (2022)
Cécile Trottet, Thijs Vogels, Martin Jaggi, Mary-Anne Hartley
Modular Clinical Decision Support Networks (MoDN) - Updatable, Interpretable, and Portable Predictions for Evolving Clinical Environments. CoRR (2022)
Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
Beyond spectral gap: the role of the topology in decentralized learning. NeurIPS (2022)
Xianyao Zhang, Marco Manzi, Thijs Vogels, Henrik Dahlberg, Markus H. Gross, Marios Papas
Deep Compositional Denoising for High-quality Monte Carlo Rendering. Comput. Graph. Forum 40 (4) (2021)
Thijs Vogels, Lie He, Anastasia Koloskova, Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi
RelaySum for Decentralized Deep Learning on Heterogeneous Data. CoRR (2021)
Thijs Vogels, Lie He, Anastasia Koloskova, Sai Praneeth Karimireddy, Tao Lin, Sebastian U. Stich, Martin Jaggi
RelaySum for Decentralized Deep Learning on Heterogeneous Data. NeurIPS (2021)
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
Practical Low-Rank Communication Compression in Decentralized Deep Learning. NeurIPS (2020)
Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret
Optimizer Benchmarking Needs to Account for Hyperparameter Tuning. ICML (2020)
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
PowerGossip: Practical Low-Rank Communication Compression in Decentralized Deep Learning. CoRR (2020)
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization. NeurIPS (2019)
Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret
On the Tunability of Optimizers in Deep Learning. CoRR (2019)
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization. CoRR (2019)
Thijs Vogels, Octavian-Eugen Ganea, Carsten Eickhoff
Web2Text: Deep Structured Boilerplate Removal. ECIR (2018)
Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Gerhard Röthlin, Alex Harvill, David Adler, Mark Meyer, Jan Novák
Denoising with kernel prediction and asymmetric loss functions. ACM Trans. Graph. 37 (4) (2018)
Thijs Vogels, Octavian-Eugen Ganea, Carsten Eickhoff
Web2Text: Deep Structured Boilerplate Removal. CoRR (2018)
Steve Bako, Thijs Vogels, Brian McWilliams, Mark Meyer, Jan Novák, Alex Harvill, Pradeep Sen, Tony DeRose, Fabrice Rousselle
Kernel-predicting convolutional networks for denoising Monte Carlo renderings. ACM Trans. Graph. 36 (4) (2017)
Cristina Kadar, Grammatiki Zanni, Thijs Vogels, Irena Pletikosa Cvijikj
Towards a Burglary Risk Profiler Using Demographic and Spatial Factors. WISE (1) (2015)