Thijs Vogels

26 papers A* 7A 1Journal 17Unranked 1
YearRankTypeTitle / Venue / Authors
2025 J jnl
Accurate and scalable exchange-correlation with deep learning.
CoRR
Giulia Luise, Chin-Wei Huang, Thijs Vogels, Derk P. Kooi, Sebastian Ehlert, Stephanie Lanius, Klaas J. H. Giesbertz, Amir Karton, Deniz Gunceler, Megan Stanley, Wessel P. Bruinsma, Lin Huang, Xinran Wei, José Garrido Torres, Abylay Katbashev, Rodrigo Chavez Zavaleta, Bálint Máté, Sékou-Oumar Kaba, Roberto Sordillo, Yingrong Chen, David B. Williams-Young, Christopher M. Bishop, Jan Hermann, Rianne van den Berg, Paola Gori-Giorgi
2024 J jnl
Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits.
CoRR
Daniel Morales-Brotons, Thijs Vogels, Hadrien Hendrikx
2024 J jnl
Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits.
Trans. Mach. Learn. Res.
Daniel Morales-Brotons, Thijs Vogels, Hadrien Hendrikx
2024 A* conf
LASER: Linear Compression in Wireless Distributed Optimization.
ICML
Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim, Michael Gastpar
2023 J jnl
Beyond Spectral Gap: The Role of the Topology in Decentralized Learning.
J. Mach. Learn. Res.
Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
2023 J jnl
Beyond spectral gap (extended): The role of the topology in decentralized learning.
CoRR
Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
2023 J jnl
LASER: Linear Compression in Wireless Distributed Optimization.
CoRR
Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim, Michael C. Gastpar
2023 A* conf
MultiMoDN - Multimodal, Multi-Task, Interpretable Modular Networks.
NeurIPS
Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels, Martin Jaggi, Tanja Käser, Mary-Anne Hartley
2023 J jnl
MultiModN- Multimodal, Multi-Task, Interpretable Modular Networks.
CoRR
Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels, Martin Jaggi, Tanja Käser, Mary-Anne Hartley
2022 J jnl
Beyond spectral gap: The role of the topology in decentralized learning.
CoRR
Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
2022 A* conf
Beyond spectral gap: the role of the topology in decentralized learning.
NeurIPS
Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
2022 J jnl
Modular Clinical Decision Support Networks (MoDN) - Updatable, Interpretable, and Portable Predictions for Evolving Clinical Environments.
CoRR
Cécile Trottet, Thijs Vogels, Martin Jaggi, Mary-Anne Hartley
2021 J jnl
Deep Compositional Denoising for High-quality Monte Carlo Rendering.
Comput. Graph. Forum
Xianyao Zhang, Marco Manzi, Thijs Vogels, Henrik Dahlberg, Markus Gross, Marios Papas
2021 A* conf
RelaySum for Decentralized Deep Learning on Heterogeneous Data.
NeurIPS
Thijs Vogels, Lie He, Anastasia Koloskova, Sai Praneeth Karimireddy, Tao Lin, Sebastian U. Stich, Martin Jaggi
2021 J jnl
RelaySum for Decentralized Deep Learning on Heterogeneous Data.
CoRR
Thijs Vogels, Lie He, Anastasia Koloskova, Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi
2020 A* conf
Optimizer Benchmarking Needs to Account for Hyperparameter Tuning.
ICML
Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret
2020 J jnl
PowerGossip: Practical Low-Rank Communication Compression in Decentralized Deep Learning.
CoRR
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
2020 A* conf
Practical Low-Rank Communication Compression in Decentralized Deep Learning.
NeurIPS
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
2019 J jnl
On the Tunability of Optimizers in Deep Learning.
CoRR
Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret
2019 A* conf
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization.
NeurIPS
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
2019 J jnl
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization.
CoRR
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi
2018 J jnl
Denoising with kernel prediction and asymmetric loss functions.
ACM Trans. Graph.
Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Gerhard Röthlin, Alex Harvill, David Adler, Mark Meyer, Jan Novák
2018 A conf
Web2Text: Deep Structured Boilerplate Removal.
ECIR
Thijs Vogels, Octavian-Eugen Ganea, Carsten Eickhoff
2018 J jnl
Web2Text: Deep Structured Boilerplate Removal.
CoRR
Thijs Vogels, Octavian-Eugen Ganea, Carsten Eickhoff
2017 J jnl
Kernel-predicting convolutional networks for denoising Monte Carlo renderings.
ACM Trans. Graph.
Steve Bako, Thijs Vogels, Brian McWilliams, Mark Meyer, Jan Novák, Alex Harvill, Pradeep Sen, Tony DeRose, Fabrice Rousselle
2015 — conf
Towards a Burglary Risk Profiler Using Demographic and Spatial Factors.
WISE (1)
Cristina Kadar, Grammatiki Zanni, Thijs Vogels, Irena Pletikosa Cvijikj