Follow
Thijs Vogels
Thijs Vogels
Microsoft Research AI for Science
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
Kernel-predicting convolutional networks for denoising Monte Carlo renderings.
S Bako, T Vogels, B McWilliams, M Meyer, J NovŠk, A Harvill, P Sen, ...
ACM Trans. Graph. 36 (4), 97:1-97:14, 2017
3242017
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization
T Vogels, SP Karimireddy, M Jaggi
NeurIPS 2019, 14259-14268, 2019
2932019
Denoising with kernel prediction and asymmetric loss functions
T Vogels, F Rousselle, B McWilliams, G RŲthlin, A Harvill, D Adler, ...
ACM Transactions on Graphics (TOG) 37 (4), 1-15, 2018
1832018
Denoising Monte Carlo renderings using machine learning with importance sampling
T Vogels, F Rousselle, B McWilliams, M Meyer, J Novak
US Patent 10,572,979, 2020
672020
Relaysum for decentralized deep learning on heterogeneous data
T Vogels, L He, A Koloskova, SP Karimireddy, T Lin, SU Stich, M Jaggi
Advances in Neural Information Processing Systems 34, 28004-28015, 2021
592021
Kernel-predicting convolutional neural networks for denoising
T Vogels, J NovŠk, F Rousselle, B McWilliams
US Patent 10,475,165, 2019
572019
Web2text: Deep structured boilerplate removal
T Vogels, OE Ganea, C Eickhoff
Advances in Information Retrieval: 40th European Conference on IR Research†…, 2018
522018
Optimizer benchmarking needs to account for hyperparameter tuning
PT Sivaprasad, F Mai, T Vogels, M Jaggi, F Fleuret
International Conference on Machine Learning, 9036-9045, 2020
51*2020
Practical low-rank communication compression in decentralized deep learning
T Vogels, SP Karimireddy, M Jaggi
Advances in Neural Information Processing Systems 33, 14171-14181, 2020
49*2020
Denoising monte carlo renderings using progressive neural networks
T Vogels, F Rousselle, B McWilliams, M Meyer, J Novak
US Patent 10,607,319, 2020
412020
Denoising Monte Carlo renderings using generative adversarial neural networks
T Vogels, F Rousselle, B McWilliams, M Meyer, J Novak
US Patent 10,586,310, 2020
282020
Denoising Monte Carlo renderings using neural networks with asymmetric loss
T Vogels, F Rousselle, J Novak, B McWilliams, M Meyer, A Harvill
US Patent 10,699,382, 2020
242020
Beyond spectral gap: The role of the topology in decentralized learning
T Vogels, H Hendrikx, M Jaggi
Advances in Neural Information Processing Systems 35, 15039-15050, 2022
232022
Deep Compositional Denoising for High‐quality Monte Carlo Rendering
X Zhang, M Manzi, T Vogels, H Dahlberg, M Gross, M Papas
Computer Graphics Forum 40 (4), 1-13, 2021
132021
Denoising Monte Carlo renderings using machine learning with importance sampling
T Vogels, F Rousselle, B McWilliams, M Meyer, J Novak
US Patent 10,789,686, 2020
122020
Multi-scale architecture of denoising monte carlo renderings using neural networks
T Vogels, F Rousselle, J Novak, B McWilliams, M Meyer, A Harvill
US Patent 10,672,109, 2020
102020
Towards a Burglary Risk Profiler Using Demographic and Spatial Factors
C Kadar, G Zanni, T Vogels, I Pletikosa
Web Information Systems Engineering (WISE) 16, 586-600, 2015
82015
Modular Clinical Decision Support Networks (MoDN)—Updatable, interpretable, and portable predictions for evolving clinical environments
C Trottet, T Vogels, K Keitel, AV Kulinkina, R Tan, L Cobuccio, M Jaggi, ...
PLOS digital health 2 (7), e0000108, 2023
52023
Adaptive sampling in Monte Carlo renderings using error-predicting neural networks
T Vogels, F Rousselle, J Novak, B McWilliams, M Meyer, A Harvill
US Patent 10,706,508, 2020
42020
MultiModN—Multimodal, Multi-Task, Interpretable Modular Networks
V Swamy, M Satayeva, J Frej, T Bossy, T Vogels, M Jaggi, T Kšser, ...
Advances in Neural Information Processing Systems 36, 2024
22024
The system can't perform the operation now. Try again later.
Articles 1–20