Παρακολούθηση
Thijs Vogels
Thijs Vogels
Microsoft Research AI for Science
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα microsoft.com - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
Έτος
PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization
T Vogels, SP Karimireddy, M Jaggi
NeurIPS 2019, 14259-14268, 2019
3702019
Kernel-predicting convolutional networks for denoising Monte Carlo renderings.
S Bako, T Vogels, B McWilliams, M Meyer, J Novák, A Harvill, P Sen, ...
ACM Trans. Graph. 36 (4), 97:1-97:14, 2017
3612017
Denoising with kernel prediction and asymmetric loss functions
T Vogels, F Rousselle, B McWilliams, G Röthlin, A Harvill, D Adler, ...
ACM Transactions on Graphics (TOG) 37 (4), 1-15, 2018
2012018
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
812020
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
702021
Kernel-predicting convolutional neural networks for denoising
T Vogels, J Novák, F Rousselle, B McWilliams
US Patent 10,475,165, 2019
682019
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
62*2020
Web2text: Deep structured boilerplate removal
T Vogels, OE Ganea, C Eickhoff
Advances in Information Retrieval: 40th European Conference on IR Research …, 2018
592018
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
57*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
492020
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
332020
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
312022
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
272020
Exponential moving average of weights in deep learning: Dynamics and benefits
D Morales-Brotons, T Vogels, H Hendrikx
Transactions on Machine Learning Research, 2024
172024
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
142021
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
142020
Temporal techniques of denoising Monte Carlo renderings using neural networks
T Vogels, F Rousselle, J Novak, B McWilliams, M Meyer, A Harvill
US Patent 11,532,073, 2022
132022
Multimodn—multimodal, multi-task, interpretable modular networks
V Swamy, M Satayeva, J Frej, T Bossy, T Vogels, M Jaggi, T Käser, ...
Advances in Neural Information Processing Systems 36, 2024
122024
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
112020
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
102015
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