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2020 – today
- 2023
[c8]Dimitri von Rütte, Luca Biggio, Yannic Kilcher, Thomas Hofmann:
FIGARO: Controllable Music Generation using Learned and Expert Features. ICLR 2023- [c7]Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi Rui Tam, Keith Stevens, Abdullah Barhoum, Duc Nguyen, Oliver Stanley, Richárd Nagyfi, Shahul ES, Sameer Suri, David Glushkov, Arnav Dantuluri, Andrew Maguire, Christoph Schuhmann, Huu Nguyen, Alexander Mattick:
OpenAssistant Conversations - Democratizing Large Language Model Alignment. NeurIPS 2023 - [i13]Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi-Rui Tam, Keith Stevens, Abdullah Barhoum, Nguyen Minh Duc, Oliver Stanley, Richárd Nagyfi, Shahul ES, Sameer Suri, David Glushkov, Arnav Dantuluri, Andrew Maguire, Christoph Schuhmann, Huu Nguyen, Alexander Mattick:
OpenAssistant Conversations - Democratizing Large Language Model Alignment. CoRR abs/2304.07327 (2023) - 2022
- [j1]Leonard Adolphs, Benjamin Börschinger, Christian Buck, Michelle Chen Huebscher, Massimiliano Ciaramita, Lasse Espeholt, Thomas Hofmann, Yannic Kilcher, Sascha Rothe, Pier Giuseppe Sessa, Lierni Sestorain:
Boosting Search Engines with Interactive Agents. Trans. Mach. Learn. Res. 2022 (2022) - [i12]Dimitri von Rütte, Luca Biggio, Yannic Kilcher, Thomas Hoffman:
FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control. CoRR abs/2201.10936 (2022) - 2021
- [b1]Yannic Kilcher:
Navigating the Latent Spaces of Deep Neural Networks using Adversarial Techniques. ETH Zurich, Zürich, Switzerland, 2021 - [i11]Paulina Grnarova, Yannic Kilcher, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann:
Generative Minimization Networks: Training GANs Without Competition. CoRR abs/2103.12685 (2021) - [i10]Leonard Adolphs, Benjamin Börschinger, Christian Buck, Michelle Chen Huebscher, Massimiliano Ciaramita, Lasse Espeholt, Thomas Hofmann, Yannic Kilcher:
Boosting Search Engines with Interactive Agents. CoRR abs/2109.00527 (2021) - 2020
- [c6]David Yenicelik, Florian Schmidt, Yannic Kilcher:
How does BERT capture semantics? A closer look at polysemous words. BlackboxNLP@EMNLP 2020: 156-162 - [c5]Kevin Roth, Yannic Kilcher, Thomas Hofmann:
Adversarial Training is a Form of Data-dependent Operator Norm Regularization. NeurIPS 2020
2010 – 2019
- 2019
- [c4]Kevin Roth, Yannic Kilcher, Thomas Hofmann:
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples. ICML 2019: 5498-5507 - [i9]Kevin Roth, Yannic Kilcher, Thomas Hofmann:
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples. CoRR abs/1902.04818 (2019) - [i8]Kevin Roth, Yannic Kilcher, Thomas Hofmann:
Adversarial Training Generalizes Data-dependent Spectral Norm Regularization. CoRR abs/1906.01527 (2019) - [i7]Benjamin Börschinger, Jordan L. Boyd-Graber, Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Michelle Chen Huebscher, Wojciech Gajewski, Yannic Kilcher, Rodrigo Nogueira, Lierni Sestorain Saralegu:
Meta Answering for Machine Reading. CoRR abs/1911.04156 (2019) - 2018
- [c3]Yannic Kilcher, Aurélien Lucchi, Thomas Hofmann:
Semantic Interpolation in Implicit Models. ICLR (Poster) 2018 - 2017
- [i6]Yannic Kilcher, Aurélien Lucchi, Thomas Hofmann:
Generator Reversal. CoRR abs/1707.09241 (2017) - [i5]Yannic Kilcher, Aurélien Lucchi, Thomas Hofmann:
Semantic Interpolation in Implicit Models. CoRR abs/1710.11381 (2017) - [i4]Yannic Kilcher, Aurélien Lucchi, Thomas Hofmann:
Flexible Prior Distributions for Deep Generative Models. CoRR abs/1710.11383 (2017) - [i3]Yannic Kilcher, Gary Bécigneul, Thomas Hofmann:
Parametrizing filters of a CNN with a GAN. CoRR abs/1710.11386 (2017) - [i2]Yannic Kilcher, Thomas Hofmann:
The best defense is a good offense: Countering black box attacks by predicting slightly wrong labels. CoRR abs/1711.05475 (2017) - 2016
- [c2]Elias Sprengel, Martin Jaggi, Yannic Kilcher, Thomas Hofmann:
Audio Based Bird Species Identification using Deep Learning Techniques. CLEF (Working Notes) 2016: 547-559 - [c1]Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M. Buhmann, Nicolai Meinshausen:
Scalable Adaptive Stochastic Optimization Using Random Projections. NIPS 2016: 1750-1758 - [i1]Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M. Buhmann, Nicolai Meinshausen:
Scalable Adaptive Stochastic Optimization Using Random Projections. CoRR abs/1611.06652 (2016)
Coauthor Index
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