Bastiaan S. Veeling

25 papers A* 6Misc 1Journal 17Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Improved motif-scaffolding with SE(3) flow matching. CoRR Jason Yim, Andrew Campbell, Emile Mathieu, Andrew Y. K. Foong, Michael Gastegger, José Jiménez-Luna, Sarah Lewis, Victor Garcia Satorras, Bastiaan S. Veeling, Frank Noé, Regina Barzilay, Tommi S. Jaakkola
2024	J	`jnl`	Improved motif-scaffolding with SE(3) flow matching. Trans. Mach. Learn. Res. Jason Yim, Andrew Campbell, Emile Mathieu, Andrew Y. K. Foong, Michael Gastegger, José Jiménez-Luna, Sarah Lewis, Victor Garcia Satorras, Bastiaan S. Veeling, Frank Noé, Regina Barzilay, Tommi S. Jaakkola
2024	A*	`conf`	Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck. ICLR Marco Federici, Patrick Forré, Ryota Tomioka, Bastiaan S. Veeling
2023	J	`jnl`	Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck. CoRR Marco Federici, Patrick Forré, Ryota Tomioka, Bastiaan S. Veeling
2023	J	`jnl`	PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers. CoRR Phillip Lippe, Bastiaan S. Veeling, Paris Perdikaris, Richard E. Turner, Johannes Brandstetter
2021	A*	`conf`	Active Deep Probabilistic Subsampling. ICML Hans Van Gorp, Iris A. M. Huijben, Bastiaan S. Veeling, Nicola Pezzotti, Ruud J. G. van Sloun
2021	J	`jnl`	Dynamic Probabilistic Pruning: A general framework for hardware-constrained pruning at different granularities. CoRR Lizeth Gonzalez-Carabarin, Iris A. M. Huijben, Bastiaan S. Veeling, Alexandre Schmid, Ruud J. G. van Sloun
2021	J	`jnl`	Towards radiologist-level cancer risk assessment in CT lung screening using deep learning. Comput. Medical Imaging Graph. Stojan Trajanovski, Dimitrios Mavroeidis, Christine Leon Swisher, Binyam Gebrekidan Gebre, Bastiaan S. Veeling, Rafael Wiemker, Tobias Klinder, Amir Tahmasebi, Shawn M. Regis, Christoph Wald, Brady J. McKee, Sebastian Flacke, Heber MacMahon, Homer H. Pien
2020	A*	`conf`	Deep probabilistic subsampling for task-adaptive compressed sensing. ICLR Iris A. M. Huijben, Bastiaan S. Veeling, Ruud J. G. van Sloun
2020	A*	`conf`	How Good is the Bayes Posterior in Deep Neural Networks Really? ICML Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	Hydra: Preserving Ensemble Diversity for Model Distillation. CoRR Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton
2020	Misc	`conf`	Learning Sampling and Model-Based Signal Recovery for Compressed Sensing MRI. ICASSP Iris A. M. Huijben, Bastiaan S. Veeling, Ruud J. G. van Sloun
2020	J	`jnl`	Learning Sampling and Model-Based Signal Recovery for Compressed Sensing MRI. CoRR Iris A. M. Huijben, Bastiaan S. Veeling, Ruud J. G. van Sloun
2020	J	`jnl`	Learning Sub-Sampling and Signal Recovery With Applications in Ultrasound Imaging. IEEE Trans. Medical Imaging Iris A. M. Huijben, Bastiaan S. Veeling, Kees Janse, Massimo Mischi, Ruud J. G. van Sloun
2020	A*	`conf`	The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. ICML Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. CoRR Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2019	J	`jnl`	Greedy InfoMax for Biologically Plausible Self-Supervised Representation Learning. CoRR Sindy Löwe, Peter O'Connor, Bastiaan S. Veeling
2019	J	`jnl`	Learning Sub-Sampling and Signal Recovery with Applications in Ultrasound Imaging. CoRR Iris A. M. Huijben, Bastiaan S. Veeling, Kees Janse, Massimo Mischi, Ruud J. G. van Sloun
2019	A*	`conf`	Putting An End to End-to-End: Gradient-Isolated Learning of Representations. NeurIPS Sindy Löwe, Peter O'Connor, Bastiaan S. Veeling
2019	J	`jnl`	Supervised Uncertainty Quantification for Segmentation with Multiple Annotations. CoRR Shi Hu, Daniel E. Worrall, Stefan Knegt, Bastiaan S. Veeling, Henkjan J. Huisman, Max Welling
2018	J	`jnl`	Predictive Uncertainty through Quantization. CoRR Bastiaan S. Veeling, Rianne van den Berg, Max Welling
2018	—	`conf`	Rotation Equivariant CNNs for Digital Pathology. MICCAI (2) Bastiaan S. Veeling, Jasper Linmans, Jim Winkens, Taco Cohen, Max Welling
2018	J	`jnl`	Rotation Equivariant CNNs for Digital Pathology. CoRR Bastiaan S. Veeling, Jasper Linmans, Jim Winkens, Taco Cohen, Max Welling
2018	J	`jnl`	Sample Efficient Semantic Segmentation using Rotation Equivariant Convolutional Networks. CoRR Jasper Linmans, Jim Winkens, Bastiaan S. Veeling, Taco S. Cohen, Max Welling