Sander Dieleman

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 50

Top Topics

Diffusion Model

Speech Synthesis

Top Venues

Publications

Alice Baird, Rachel Manzelli, Panagiotis Tzirakis, Chris Gagne, Haoqi Li, Sadie Allen, Sander Dieleman, Brian Kulis, Shrikanth S. Narayanan, Alan Cowen
The NeurIPS 2023 Machine Learning for Audio Workshop: Affective Audio Benchmarks and Novel Data. CoRR (2024)
Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Grathwohl
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. CoRR (2023)
Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Sussman Grathwohl
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC. ICML (2023)
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
Towards Learning Universal Audio Representations. ICASSP (2022)
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
Continuous diffusion for categorical data. CoRR (2022)
Curtis Hawthorne, Andrew Jaegle, Catalina Cangea, Sebastian Borgeaud, Charlie Nash, Mateusz Malinowski, Sander Dieleman, Oriol Vinyals, Matthew Botvinick, Ian Simon, Hannah Sheahan, Neil Zeghidour, Jean-Baptiste Alayrac, João Carreira, Jesse H. Engel
General-purpose, long-context autoregressive modeling with Perceiver AR. CoRR (2022)
Robin Strudel, Corentin Tallec, Florent Altché, Yilun Du, Yaroslav Ganin, Arthur Mensch, Will Grathwohl, Nikolay Savinov, Sander Dieleman, Laurent Sifre, Rémi Leblond
Self-conditioned Embedding Diffusion for Text Generation. CoRR (2022)
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
General-purpose, long-context autoregressive modeling with Perceiver AR. ICML (2022)
Pierre H. Richemond, Sander Dieleman, Arnaud Doucet
Categorical SDEs with Simplex Diffusion. CoRR (2022)
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
Towards Learning Universal Audio Representations. CoRR (2021)
Jeff Donahue, Sander Dieleman, Mikolaj Binkowski, Erich Elsen, Karen Simonyan
End-to-end Adversarial Text-to-Speech. ICLR (2021)
Charlie Nash, Jacob Menick, Sander Dieleman, Peter W. Battaglia
Generating images with sparse representations. ICML (2021)
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
A Deep Learning Approach for Characterizing Major Galaxy Mergers. CoRR (2021)
Sander Dieleman, Charlie Nash, Jesse H. Engel, Karen Simonyan
Variable-rate discrete representation learning. CoRR (2021)
Charlie Nash, Jacob Menick, Sander Dieleman, Peter W. Battaglia
Generating Images with Sparse Representations. CoRR (2021)
Mikolaj Binkowski, Jeff Donahue, Sander Dieleman, Aidan Clark, Erich Elsen, Norman Casagrande, Luis C. Cobo, Karen Simonyan
High Fidelity Speech Synthesis with Adversarial Networks. ICLR (2020)
Sageev Oore, Ian Simon, Sander Dieleman, Douglas Eck, Karen Simonyan
This time with feeling: learning expressive musical performance. Neural Comput. Appl. 32 (4) (2020)
Pauline Luc, Aidan Clark, Sander Dieleman, Diego de Las Casas, Yotam Doron, Albin Cassirer, Karen Simonyan
Transformation-based Adversarial Video Prediction on Large-Scale Data. CoRR (2020)
Jeff Donahue, Sander Dieleman, Mikolaj Binkowski, Erich Elsen, Karen Simonyan
End-to-End Adversarial Text-to-Speech. CoRR (2020)
Jean-Baptiste Alayrac, Adrià Recasens, Rosalia Schneider, Relja Arandjelovic, Jason Ramapuram, Jeffrey De Fauw, Lucas Smaira, Sander Dieleman, Andrew Zisserman
Self-Supervised MultiModal Versatile Networks. NeurIPS (2020)
Jean-Baptiste Alayrac, Adrià Recasens, Rosalia Schneider, Relja Arandjelovic, Jason Ramapuram, Jeffrey De Fauw, Lucas Smaira, Sander Dieleman, Andrew Zisserman
Self-Supervised MultiModal Versatile Networks. CoRR (2020)
Jamie Hayes, Krishnamurthy Dvijotham, Yutian Chen, Sander Dieleman, Pushmeet Kohli, Norman Casagrande
Towards transformation-resilient provenance detection of digital media. CoRR (2020)
Curtis Hawthorne, Andriy Stasyuk, Adam Roberts, Ian Simon, Cheng-Zhi Anna Huang, Sander Dieleman, Erich Elsen, Jesse H. Engel, Douglas Eck
Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset. ICLR (2019)
Jeffrey De Fauw, Sander Dieleman, Karen Simonyan
Hierarchical Autoregressive Image Models with Auxiliary Decoders. CoRR (2019)
Chris Donahue, Ian Simon, Sander Dieleman
Piano Genie. IUI (2019)
Mikolaj Binkowski, Jeff Donahue, Sander Dieleman, Aidan Clark, Erich Elsen, Norman Casagrande, Luis C. Cobo, Karen Simonyan
High Fidelity Speech Synthesis with Adversarial Networks. CoRR (2019)
Curtis Hawthorne, Andriy Stasyuk, Adam Roberts, Ian Simon, Cheng-Zhi Anna Huang, Sander Dieleman, Erich Elsen, Jesse H. Engel, Douglas Eck
Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset. CoRR (2018)
Lionel Pigou, Aäron van den Oord, Sander Dieleman, Mieke Van Herreweghe, Joni Dambre
Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video. Int. J. Comput. Vis. 126 (2-4) (2018)
Sander Dieleman, Aäron van den Oord, Karen Simonyan
The challenge of realistic music generation: modelling raw audio at scale. NeurIPS (2018)
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
Parallel WaveNet: Fast High-Fidelity Speech Synthesis. ICML (2018)
Nal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg, Aäron van den Oord, Sander Dieleman, Koray Kavukcuoglu
Efficient Neural Audio Synthesis. ICML (2018)
Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Bracha Shapira, Domonkos Tikk, Flavian Vasile, Sander Dieleman
DLRS 2018: third workshop on deep learning for recommender systems. RecSys (2018)
Sander Dieleman, Aäron van den Oord, Karen Simonyan
The challenge of realistic music generation: modelling raw audio at scale. CoRR (2018)
Sageev Oore, Ian Simon, Sander Dieleman, Douglas Eck, Karen Simonyan
This Time with Feeling: Learning Expressive Musical Performance. CoRR (2018)
Chris Donahue, Ian Simon, Sander Dieleman
Piano Genie. CoRR (2018)
Nal Kalchbrenner, Erich Elsen, Karen Simonyan, Seb Noury, Norman Casagrande, Edward Lockhart, Florian Stimberg, Aäron van den Oord, Sander Dieleman, Koray Kavukcuoglu
Efficient Neural Audio Synthesis. CoRR (2018)
Jesse H. Engel, Cinjon Resnick, Adam Roberts, Sander Dieleman, Mohammad Norouzi, Douglas Eck, Karen Simonyan
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders. ICML (2017)
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
Parallel WaveNet: Fast High-Fidelity Speech Synthesis. CoRR (2017)
Jesse H. Engel, Cinjon Resnick, Adam Roberts, Sander Dieleman, Douglas Eck, Karen Simonyan, Mohammad Norouzi
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders. CoRR (2017)
Balázs Hidasi, Alexandros Karatzoglou, Oren Sar Shalom, Sander Dieleman, Bracha Shapira, Domonkos Tikk
DLRS 2017: Second Workshop on Deep Learning for Recommender Systems. RecSys (2017)
Aäron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew W. Senior, Koray Kavukcuoglu
WaveNet: A Generative Model for Raw Audio. SSW (2016)
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
Mastering the game of Go with deep neural networks and tree search. Nat. 529 (7587) (2016)
Sander Dieleman
Keynote: Deep learning for audio-based music recommendation. DLRS@RecSys (2016)
Aäron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew W. Senior, Koray Kavukcuoglu
WaveNet: A Generative Model for Raw Audio. CoRR (2016)
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
Theano: A Python framework for fast computation of mathematical expressions. CoRR (2016)
Sander Dieleman, Jeffrey De Fauw, Koray Kavukcuoglu
Exploiting Cyclic Symmetry in Convolutional Neural Networks. ICML (2016)
Sander Dieleman, Jeffrey De Fauw, Koray Kavukcuoglu
Exploiting Cyclic Symmetry in Convolutional Neural Networks. CoRR (2016)
Jonas Degrave, Sander Dieleman, Joni Dambre, Francis Wyffels
Spatial Chirp-Z Transformer Networks. ESANN (2016)
Sander Dieleman, Kyle W. Willett, Joni Dambre
Rotation-invariant convolutional neural networks for galaxy morphology prediction. CoRR (2015)
Lionel Pigou, Aäron van den Oord, Sander Dieleman, Mieke Van Herreweghe, Joni Dambre
Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video. CoRR (2015)
Lionel Pigou, Sander Dieleman, Pieter-Jan Kindermans, Benjamin Schrauwen
Sign Language Recognition Using Convolutional Neural Networks. ECCV Workshops (1) (2014)
Aäron van den Oord, Sander Dieleman, Benjamin Schrauwen
Transfer Learning by Supervised Pre-training for Audio-based Music Classification. ISMIR (2014)
Sander Dieleman, Benjamin Schrauwen
End-to-end learning for music audio. ICASSP (2014)
Sander Dieleman, Benjamin Schrauwen
Multiscale Approaches To Music Audio Feature Learning. ISMIR (2013)
Ken Caluwaerts, Francis Wyffels, Sander Dieleman, Benjamin Schrauwen
The spectral radius remains a valid indicator of the Echo state property for large reservoirs. IJCNN (2013)
Aäron van den Oord, Sander Dieleman, Benjamin Schrauwen
Deep content-based music recommendation. NIPS (2013)
Philemon Brakel, Sander Dieleman, Benjamin Schrauwen
Training Restricted Boltzmann Machines with Multi-tempering: Harnessing Parallelization. ICANN (2) (2012)
David Verstraeten, Benjamin Schrauwen, Sander Dieleman, Philemon Brakel, Pieter Buteneers, Dejan Pecevski
Oger: modular learning architectures for large-scale sequential processing. J. Mach. Learn. Res. 13 (2012)
Sander Dieleman, Philemon Brakel, Benjamin Schrauwen
Audio-based Music Classification with a Pretrained Convolutional Network. ISMIR (2011)