Sander Dieleman

According to our database, Sander Dieleman authored at least 42 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

The NeurIPS 2023 Machine Learning for Audio Workshop: Affective Audio Benchmarks and Novel Data.

Alice Baird, Rachel Manzelli, Panagiotis Tzirakis, Chris Gagne, Haoqi Li, Sadie Allen, Sander Dieleman, Brian Kulis, Shrikanth S. Narayanan, Alan Cowen

CoRR, 2024

2023

Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC.

Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Sussman Grathwohl

Proceedings of the International Conference on Machine Learning, 2023

2022

Continuous diffusion for categorical data.

Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H. Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, Curtis Hawthorne, Rémi Leblond, Will Grathwohl, Jonas Adler

CoRR, 2022

Self-conditioned Embedding Diffusion for Text Generation.

Robin Strudel, Corentin Tallec, Florent Altché, Yilun Du, Yaroslav Ganin, Arthur Mensch, Will Grathwohl, Nikolay Savinov, Sander Dieleman, Laurent Sifre, Rémi Leblond

CoRR, 2022

Categorical SDEs with Simplex Diffusion.

Pierre H. Richemond, Sander Dieleman, Arnaud Doucet

CoRR, 2022

General-purpose, long-context autoregressive modeling with Perceiver AR.

Curtis Hawthorne, Andrew Jaegle, Catalina Cangea, Sebastian Borgeaud, Charlie Nash, Mateusz Malinowski, Sander Dieleman, Oriol Vinyals, Matthew M. Botvinick, Ian Simon, Hannah Sheahan, Neil Zeghidour, Jean-Baptiste Alayrac, João Carreira, Jesse H. Engel

Proceedings of the International Conference on Machine Learning, 2022

Towards Learning Universal Audio Representations.

Luyu Wang, Pauline Luc, Yan Wu, Adrià Recasens, Lucas Smaira, Andrew Brock, Andrew Jaegle, Jean-Baptiste Alayrac, Sander Dieleman, João Carreira, Aäron van den Oord

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Variable-rate discrete representation learning.

Sander Dieleman, Charlie Nash, Jesse H. Engel, Karen Simonyan

CoRR, 2021

A Deep Learning Approach for Characterizing Major Galaxy Mergers.

Skanda Koppula, Victor Bapst, Marc Huertas-Company, Sam Blackwell, Agnieszka Grabska-Barwinska, Sander Dieleman, Andrea Huber, Natasha Antropova, Mikolaj Binkowski, Hannah Openshaw, Adrià Recasens, Fernando Caro, Avishai Deke, Yohan Dubois, Jesus Vega Ferrero, David C. Koo, Joel R. Primack, Trevor Back

CoRR, 2021

Generating images with sparse representations.

Charlie Nash, Jacob Menick, Sander Dieleman, Peter W. Battaglia

Proceedings of the 38th International Conference on Machine Learning, 2021

End-to-end Adversarial Text-to-Speech.

Jeff Donahue, Sander Dieleman, Mikolaj Binkowski, Erich Elsen, Karen Simonyan

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

This time with feeling: learning expressive musical performance.

Sageev Oore, Ian Simon, Sander Dieleman, Douglas Eck, Karen Simonyan

Neural Comput. Appl., 2020

Towards transformation-resilient provenance detection of digital media.

Jamie Hayes, Krishnamurthy Dvijotham, Yutian Chen, Sander Dieleman, Pushmeet Kohli, Norman Casagrande

CoRR, 2020

Transformation-based Adversarial Video Prediction on Large-Scale Data.

Pauline Luc, Aidan Clark, Sander Dieleman, Diego de Las Casas, Yotam Doron, Albin Cassirer, Karen Simonyan

CoRR, 2020

Self-Supervised MultiModal Versatile Networks.

Jean-Baptiste Alayrac, Adrià Recasens, Rosalia Schneider, Relja Arandjelovic, Jason Ramapuram, Jeffrey De Fauw, Lucas Smaira, Sander Dieleman, Andrew Zisserman

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

High Fidelity Speech Synthesis with Adversarial Networks.

Mikolaj Binkowski, Jeff Donahue, Sander Dieleman, Aidan Clark, Erich Elsen, Norman Casagrande, Luis C. Cobo, Karen Simonyan

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Hierarchical Autoregressive Image Models with Auxiliary Decoders.

Jeffrey De Fauw, Sander Dieleman, Karen Simonyan

CoRR, 2019

Piano Genie.

Chris Donahue, Ian Simon, Sander Dieleman

Proceedings of the 24th International Conference on Intelligent User Interfaces, 2019

Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset.

Curtis Hawthorne, Andriy Stasyuk, Adam Roberts, Ian Simon, Cheng-Zhi Anna Huang, Sander Dieleman, Erich Elsen, Jesse H. Engel, Douglas Eck

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video.

Lionel Pigou, Aäron van den Oord, Sander Dieleman, Mieke Van Herreweghe, Joni Dambre

Int. J. Comput. Vis., 2018

DLRS 2018: third workshop on deep learning for recommender systems.

Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Bracha Shapira, Domonkos Tikk, Flavian Vasile, Sander Dieleman

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

The challenge of realistic music generation: modelling raw audio at scale.

Sander Dieleman, Aäron van den Oord, Karen Simonyan

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Parallel WaveNet: Fast High-Fidelity Speech Synthesis.

Aäron van den Oord, Yazhe Li, Igor Babuschkin, Karen Simonyan, Oriol Vinyals, Koray Kavukcuoglu, George van den Driessche, Edward Lockhart, Luis C. Cobo, Florian Stimberg, Norman Casagrande, Dominik Grewe, Seb Noury, Sander Dieleman, Erich Elsen, Nal Kalchbrenner, Heiga Zen, Alex Graves, Helen King, Tom Walters, Dan Belov, Demis Hassabis

Proceedings of the 35th International Conference on Machine Learning, 2018

Efficient Neural Audio Synthesis.

Nal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg, Aäron van den Oord, Sander Dieleman, Koray Kavukcuoglu

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

DLRS 2017: Second Workshop on Deep Learning for Recommender Systems.

Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Sander Dieleman, Bracha Shapira, Domonkos Tikk

Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders.

Jesse H. Engel, Cinjon Resnick, Adam Roberts, Sander Dieleman, Mohammad Norouzi, Douglas Eck, Karen Simonyan

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Mastering the game of Go with deep neural networks and tree search.

David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Vedavyas Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy P. Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel, Demis Hassabis

Nat., 2016

Theano: A Python framework for fast computation of mathematical expressions.

Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

CoRR, 2016

WaveNet: A Generative Model for Raw Audio.

Aäron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew W. Senior, Koray Kavukcuoglu

Proceedings of the 9th ISCA Speech Synthesis Workshop, 2016

Keynote: Deep learning for audio-based music recommendation.

Sander Dieleman

Proceedings of the 1st Workshop on Deep Learning for Recommender Systems, 2016

Exploiting Cyclic Symmetry in Convolutional Neural Networks.

Sander Dieleman, Jeffrey De Fauw, Koray Kavukcuoglu

Proceedings of the 33nd International Conference on Machine Learning, 2016

Spatial Chirp-Z Transformer Networks.

Jonas Degrave, Sander Dieleman, Joni Dambre, Francis Wyffels

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015

Rotation-invariant convolutional neural networks for galaxy morphology prediction.

Sander Dieleman, Kyle W. Willett, Joni Dambre

CoRR, 2015

2014

Transfer Learning by Supervised Pre-training for Audio-based Music Classification.

Aäron van den Oord, Sander Dieleman, Benjamin Schrauwen

Proceedings of the 15th International Society for Music Information Retrieval Conference, 2014

End-to-end learning for music audio.

Sander Dieleman, Benjamin Schrauwen

Proceedings of the IEEE International Conference on Acoustics, 2014

Sign Language Recognition Using Convolutional Neural Networks.

Lionel Pigou, Sander Dieleman, Pieter-Jan Kindermans, Benjamin Schrauwen

Proceedings of the Computer Vision - ECCV 2014 Workshops, 2014

2013

Deep content-based music recommendation.

Aäron van den Oord, Sander Dieleman, Benjamin Schrauwen

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Multiscale Approaches To Music Audio Feature Learning.

Sander Dieleman, Benjamin Schrauwen

Proceedings of the 14th International Society for Music Information Retrieval Conference, 2013

The spectral radius remains a valid indicator of the Echo state property for large reservoirs.

Ken Caluwaerts, Francis Wyffels, Sander Dieleman, Benjamin Schrauwen

Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

2012

Oger: modular learning architectures for large-scale sequential processing.

David Verstraeten, Benjamin Schrauwen, Sander Dieleman, Philemon Brakel, Pieter Buteneers, Dejan Pecevski

J. Mach. Learn. Res., 2012

Training Restricted Boltzmann Machines with Multi-tempering: Harnessing Parallelization.

Philemon Brakel, Sander Dieleman, Benjamin Schrauwen

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

2011

Audio-based Music Classification with a Pretrained Convolutional Network.

Sander Dieleman, Philemon Brakel, Benjamin Schrauwen

Proceedings of the 12th International Society for Music Information Retrieval Conference, 2011