| COIN: COmpression with Implicit Neural representations E Dupont*, A Goliński*, M Alizadeh, YW Teh, A Doucet ICLR 2021 Neural Compression Workshop, 2021 | 237 | 2021 |
| COIN++: Neural Compression Across Modalities E Dupont*, H Loya*, M Alizadeh, A Goliński, YW Teh, A Doucet TMLR 2022 (11), 2022 | 113* | 2022 |
| Feedback Recurrent Autoencoder for Video Compression A Golinski*, R Pourreza*, Y Yang*, G Sautiere, TS Cohen ACCV 2020, 2020 | 63 | 2020 |
| Faithful Inversion of Generative Models for Effective Amortized Inference S Webb, A Golinski, R Zinkov, N Siddharth, T Rainforth, YW Teh, F Wood NeurIPS 2018, 2018 | 53 | 2018 |
| LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood P Tempczyk, R Michaluk, Ł Garncarek, P Spurek, J Tabor, A Goliński ICML 2022, 2022 | 26 | 2022 |
| Modular System Including Multiple Detachable Sensors LL Pietrasik, AW Golinski, FM Kaklin, AH Zaatari, DJ Yee, ... US Patent App. 15/043,553, 2016 | 21 | 2016 |
| Video compression using recurrent-based machine learning systems AW Golinski, Y Yang, R Pourreza, GK Sautiere, TJ Van Rozendaal, ... US Patent 11,405,626, 2022 | 20 | 2022 |
| Improving normalizing flows via better orthogonal parameterizations A Golinski*, M Lezcano-Casado*, T Rainforth ICML 2019 Workshop on Invertible Neural Networks and Normalizing Flows, 2019 | 16 | 2019 |
| Modular Sensor Systems LL Pietrasik, AW Golinski, FM Kaklin, AH Zaatari, DJ Yee, ... US Patent App. 15/431,584, 2017 | 16 | 2017 |
| Target–Aware Bayesian Inference: How to Beat Optimal Conventional Estimators T Rainforth*, A Golinski*, F Wood, S Zaidi JMLR 21, 2020 | 13 | 2020 |
| The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning BR Gálvez, A Blaas, P Rodriguez, A Golinski, X Suau, J Ramapuram, ... ICML 2023, 2023 | 12 | 2023 |
| Amortized Monte Carlo Integration A Golinski*, F Wood, T Rainforth* ICML 2019, Best Paper Honourable Mention, 2019 | 8 | 2019 |
| Efficient and Effective Uncertainty Quantification for LLMs M Xiong, A Santilli, M Kirchhof, A Golinski, S Williamson NeurIPS 2024 Safe Generative AI Workshop, 2024 | 2 | 2024 |
| Expectation programming: Adapting probabilistic programming systems to estimate expectations efficiently T Reichelt, A Goliński, L Ong, T Rainforth UAI 2022, 2022 | 2 | 2022 |
| Lossless Compression using Continuously-Indexed Normalizing Flows A Golinski*, AL Caterini* ICLR 2021 Neural Compression Workshop, 2021 | 2 | 2021 |
| On a Spurious Interaction between Uncertainty Scores and Answer Evaluation Metrics in Generative QA Tasks A Santilli, M Xiong, M Kirchhof, P Rodriguez, F Danieli, X Suau, ... NeurIPS 2024 Safe Generative AI Workshop, 2024 | 1 | 2024 |
| Considerations for Distribution Shift Robustness of Diagnostic Models in Healthcare A Blaas, A Goliński, A Miller, L Zappella, JH Jacobsen, C Heinze-Deml arXiv preprint arXiv:2410.19575, 2024 | | 2024 |
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindE-mailová adresa ověřena na: stats.ox.ac.uk
