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Jakub Swiatkowski
Jakub Swiatkowski
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How good is the bayes posterior in deep neural networks really?
F Wenzel, K Roth, BS Veeling, J Świątkowski, L Tran, S Mandt, J Snoek, ...
International Conference on Machine Learning (ICML), 37, 2020
2702020
Discriminative k-shot learning using probabilistic models
M Bauer, M Rojas-Carulla, JB Świątkowski, B Schölkopf, RE Turner
2nd Bayesian Deep Learning Workshop, NIPS 2017, 2017
792017
The k-tied normal distribution: A compact parameterization of gaussian mean field posteriors in bayesian neural networks
J Swiatkowski, K Roth, B Veeling, L Tran, J Dillon, J Snoek, S Mandt, ...
International Conference on Machine Learning (ICML), 37, 9289-9299, 2020
402020
Hydra: Preserving ensemble diversity for model distillation
L Tran, BS Veeling, K Roth, J Swiatkowski, JV Dillon, J Snoek, S Mandt, ...
Uncertainty & Robustness in Deep Learning Workshop, ICML 2020, 2020
382020
Improved GQ-CNN: Deep learning model for planning robust grasps
M Jaśkowski, J Świątkowski, M Zając, M Klimek, J Potiuk, P Rybicki, ...
arXiv preprint arXiv:1802.05992, 2018
72018
Continuous control with ensemble deep deterministic policy gradients
P Januszewski, M Olko, M Królikowski, J Świątkowski, M Andrychowicz, ...
arXiv preprint arXiv:2111.15382, 2021
32021
Bayesian Neural Networks for K-Shot Learning
JB Świątkowski
2017
Three-tier web application for medical clinics
J Świątkowski
Instytut Mikroelektroniki i Optoelektroniki, 2014
2014
Supplementary Materials for: The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks
J Swiatkowski, K Roth, BS Veeling, L Tran, JV Dillon, J Snoek, S Mandt, ...
On the Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks
J Świątkowski, K Roth, BS Veeling, L Tran, JV Dillon, J Snoek, S Mandt, ...
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