Abstract is missing.
- Understanding Out-of-distribution: A Perspective of Data DynamicsDyah Adila, Dongyeop Kang. 1-8 [doi]
- Challenges of Adversarial Image AugmentationsArno Blaas, Xavier Suau, Jason Ramapuram, Nicholas Apostoloff, Luca Zappella. 9-14 [doi]
- Shape DefenseAli Borji. 15-20 [doi]
- Entropic Issues in Likelihood-Based OOD DetectionAnthony L. Caterini, Gabriel Loaiza-Ganem. 21-26 [doi]
- Is the Number of Trainable Parameters All That Actually Matters?Amélie Chatelain, Amine Djeghri, Daniel Hesslow, Julien Launay. 27-32 [doi]
- Unit-level surprise in neural networksCian Eastwood, Ian Mason, Christopher K. I. Williams. 33-40 [doi]
- The Curse of Depth in Kernel RegimeSoufiane Hayou, Arnaud Doucet, Judith Rousseau. 41-47 [doi]
- Text Ranking and Classification using Data CompressionNitya Kasturi, Igor L. Markov. 48-53 [doi]
- Nonlinear Denoising, Linear DemixingRainer Kelz, Gerhard Widmer. 54-58 [doi]
- Addressing Bias in Active Learning with Depth Uncertainty Networks... or NotChelsea Murray, James Urquhart Allingham, Javier Antorán, José Miguel Hernández-Lobato. 59-63 [doi]
- CDF Normalization for Controlling the Distribution of Hidden NodesMike Van Ness, Madeleine Udell. 64-68 [doi]
- The Beauty Everywhere: How Aesthetic Criteria Contribute to the Development of AIPaulo Pirozelli, João F. N. Cortese. 69-74 [doi]
- Causal Inference, is just Inference: A beautifully simple idea that not everyone acceptsDavid Rohde. 75-79 [doi]
- GOPHER: Categorical probabilistic forecasting with graph structure via local continuous-time dynamicsKe Alexander Wang, Danielle C. Maddix, Yuyang Wang. 80-85 [doi]