Hi, I'm Yannic Kilcher

Yannic Kilcher

About me

I'm a Machine Learning researcher and engineer. I also run a YouTube channel dedicated to AI research.

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Content

YouTube Channel

I make videos about recent developments in Machine Learning research, such as paper analyses, fun projects, and the infamous ML News.

Latest Video

Alternative Uplaods

(coming soon)

Community Paper Feed

The Community Paper Feed is a distributed effort to discover and share interesting research on Twitter. Anyone can submit a paper from ArXiv or an existing Tweet to the feed. Submissions are manually reviewed.

Submit to the Feed

Merchandise

Channel themed merch! This is regularly updated and a great way to support the channel and get something fancy in return.

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Yannic Out Of Distribution (Second Channel)

Yannic OOD is a place for random content. Feel free to watch, but don't tell me I didn't warn you 😉.

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Discord

On Discord, we talk about all things Machine Learning and beyond. We have help sections for people who seek advice, as well as sections for research topics and promotional material. We also host regular paper discussions on our voice chat.

Join the Discord

Support Me

The best way to support me is to share out the content. Below are also some ways to support me financially:

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Academic Publications

Generative Minimization Networks: Training GANs Without Competition
2021, Grnarova, Paulina; Kilcher, Yannic; Levy, Kfir Y; Lucchi, Aurelien; Hofmann, Thomas;

Machine-learning Based Automatic Formulation of Query Sequences to Improve Search
2021, Ciaramita, Massimiliano; Huebscher, Michelle Chen; Boerschinger, Benjamin; Kilcher, Yannic;

Navigating the Latent Spaces of Deep Neural Networks using Adversarial Techniques
2021, Kilcher, Yannic;

Boosting search engines with interactive agents
2021, Adolphs, Leonard; Boerschinger, Benjamin; Buck, Christian; Huebscher, Michelle Chen; Ciaramita, Massimiliano; Espeholt, Lasse; Hofmann, Thomas; Kilcher, Yannic;

Rethinking Neural Networks With Benford's Law
2021, Sahu, Surya Kant; Java, Abhinav; Shaikh, Arshad; Kilcher, Yannic;

How does BERT capture semantics? A closer look at polysemous words
2020, Yenicelik, David; Schmidt, Florian; Kilcher, Yannic;

The odds are odd: A statistical test for detecting adversarial examples
2019, Roth, Kevin; Kilcher, Yannic; Hofmann, Thomas;

Adversarial training generalizes data-dependent spectral norm regularization
2019, Roth, Kevin; Kilcher, Yannic; Hofmann, Thomas;

Meta answering for machine reading
2019, Borschinger, Benjamin; Boyd-Graber, Jordan; Buck, Christian; Bulian, Jannis; Ciaramita, Massimiliano; Huebscher, Michelle Chen; Gajewski, Wojciech; Kilcher, Yannic; Nogueira, Rodrigo; Saralegu, Lierni Sestorain;

Adversarial training is a form of data-dependent operator norm regularization
2019, Roth, Kevin; Kilcher, Yannic; Hofmann, Thomas;

Escaping Flat Areas via Function-Preserving Structural Network Modifications
2018, Kilcher, Yannic; BĂ©cigneul, Gary; Hofmann, Thomas;

Parametrizing filters of a CNN with a GAN
2017, Kilcher, Yannic; Becigneul, Gary; Hofmann, Thomas;

Flexible Prior Distributions for Deep Generative Models
2017, Kilcher, Yannic; Lucchi, Aurelien; Hofmann, Thomas;

Generator Reversal
2017, Kilcher, Yannic; Lucchi, Aurélien; Hofmann, Thomas;

Semantic interpolation in implicit models
2017, Kilcher, Yannic; Lucchi, Aurélien; Hofmann, Thomas;

The best defense is a good offense: Countering black box attacks by predicting slightly wrong labels
2017, Kilcher, Yannic; Hofmann, Thomas;

Audio based bird species identification using deep learning techniques
2016, Sprengel, Elias; Jaggi, Martin; Kilcher, Yannic; Hofmann, Thomas;

Scalable adaptive stochastic optimization using random projections
2016, Krummenacher, Gabriel; McWilliams, Brian; Kilcher, Yannic; Buhmann, Joachim M; Meinshausen, Nicolai;