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Yarin Gal

Identifiers

  • name variant Yarin Gal 0.60 · backfill

Papers (44)

  1. Gaming AI-Assisted Peer Reviews Poses New Risks to the Scientific Community cs.CL · 2026 · author #5
  2. Building Reliable Long-Form Generation via Hallucination Rejection Sampling cs.CL · 2026 · author #5
  3. The Neural Tangent Kernel for Classification cs.LG · 2026 · author #4
  4. Selective Safety Steering via Value-Filtered Decoding cs.LG · 2026 · author #4
  5. Muon is Not That Special: Random or Inverted Spectra Work Just as Well cs.LG · 2026 · author #8
  6. Training Transformers for KV Cache Compressibility cs.LG · 2026 · author #4
  7. Uncertainty Quantification for LLM Function-Calling cs.CL · 2026 · author #6
  8. Richer Bayesian Last Layers with Subsampled NTK Features cs.LG · 2026 · author #5
  9. AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents cs.LG · 2024 · author #13
  10. Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs cs.CL · 2024 · author #6
  11. The Curse of Recursion: Training on Generated Data Makes Models Forget cs.LG · 2023 · author #4
  12. Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation cs.CL · 2023 · author #2
  13. Generalizing from a few environments in safety-critical reinforcement learning cs.LG · 2019 · author #4
  14. Towards Inverse Reinforcement Learning for Limit Order Book Dynamics cs.LG · 2019 · author #5
  15. An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval astro-ph.EP · 2019 · author #7
  16. Differentially Private Continual Learning stat.ML · 2019 · author #2
  17. A Unifying Bayesian View of Continual Learning stat.ML · 2019 · author #2
  18. Evaluating Bayesian Deep Learning Methods for Semantic Segmentation cs.CV · 2018 · author #2
  19. On the Importance of Strong Baselines in Bayesian Deep Learning cs.LG · 2018 · author #3
  20. Evaluating Uncertainty Quantification in End-to-End Autonomous Driving Control cs.LG · 2018 · author #3
  21. Bayesian Deep Learning for Exoplanet Atmospheric Retrieval astro-ph.EP · 2018 · author #7
  22. Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam stat.ML · 2018 · author #5
  23. Sufficient Conditions for Idealised Models to Have No Adversarial Examples: a Theoretical and Empirical Study with Bayesian Neural Networks stat.ML · 2018 · author #1
  24. Towards Robust Evaluations of Continual Learning stat.ML · 2018 · author #2
  25. Loss-Calibrated Approximate Inference in Bayesian Neural Networks stat.ML · 2018 · author #3
  26. Understanding Measures of Uncertainty for Adversarial Example Detection stat.ML · 2018 · author #2
  27. BRUNO: A Deep Recurrent Model for Exchangeable Data stat.ML · 2018 · author #4
  28. Vprop: Variational Inference using RMSprop stat.ML · 2017 · author #4
  29. Real Time Image Saliency for Black Box Classifiers stat.ML · 2017 · author #2
  30. Concrete Dropout stat.ML · 2017 · author #1
  31. Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics cs.CV · 2017 · author #2
  32. What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? cs.CV · 2017 · author #2
  33. Dropout Inference in Bayesian Neural Networks with Alpha-divergences cs.LG · 2017 · author #2
  34. Deep Bayesian Active Learning with Image Data cs.LG · 2017 · author #1
  35. A Theoretically Grounded Application of Dropout in Recurrent Neural Networks stat.ML · 2015 · author #1
  36. Dirichlet Fragmentation Processes stat.ML · 2015 · author #2
  37. Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference stat.ML · 2015 · author #1
  38. Dropout as a Bayesian Approximation: Appendix stat.ML · 2015 · author #1
  39. Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning stat.ML · 2015 · author #1
  40. Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs stat.ML · 2015 · author #1
  41. Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data stat.ML · 2015 · author #1
  42. Semantics, Modelling, and the Problem of Representation of Meaning -- a Brief Survey of Recent Literature cs.CL · 2014 · author #1
  43. Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models - a Gentle Tutorial stat.ML · 2014 · author #1
  44. Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models stat.ML · 2014 · author #1

Mentions

  • 2606.10159 #5 · arxiv_oai · confidence 0.70 Yarin Gal
  • 1509.04781 #2 · backfill · confidence 0.70 Yarin Gal
  • 1506.02158 #1 · backfill · confidence 0.70 Yarin Gal
  • 1506.02157 #1 · backfill · confidence 0.70 Yarin Gal
  • 1506.02142 #1 · backfill · confidence 0.70 Yarin Gal
  • 2606.03628 #5 · arxiv_oai · confidence 0.70 Yarin Gal
  • 1503.02424 #1 · backfill · confidence 0.70 Yarin Gal
  • 1503.02182 #1 · backfill · confidence 0.70 Yarin Gal
  • 1402.7265 #1 · backfill · confidence 0.70 Yarin Gal
  • 1402.1412 #1 · backfill · confidence 0.70 Yarin Gal
  • 1402.1389 #1 · backfill · confidence 0.70 Yarin Gal
  • 2602.01279 #5 · arxiv_oai · confidence 0.70 Yarin Gal
  • 2305.17493 #4 · arxiv_oai · confidence 0.70 Yarin Gal
  • 2605.17606 #4 · arxiv_oai · confidence 0.70 Yarin Gal
  • 2406.15927 #6 · arxiv_oai · confidence 0.70 Yarin Gal

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