The next NeurIPS conference is scheduled to take place in New Orleans from Sunday, December 10th – Saturday, December 16th, 2023.
The NeurIPS conference is one of the major worldwide annual appointments in the field of AI. The conference was founded in 1987 and is now a multi-track interdisciplinary meeting that includes invited talks, demonstrations, symposia, and oral and poster presentations of refereed papers. Along with the conference is a professional exposition focusing on machine learning in practice, a series of tutorials, and topical workshops that provide a less formal setting for the exchange of ideas.
This year, many TAILOR scientists will participate in the conference, both in different tracks and/or satellite workshops. Here is the list of the accepted papers and their authors:
1. Emanuele Sansone. The Triad of Failure Modes and a Possible Way Out. NeurIPS 2023 Workshop Self-Supervised Learning – Theory and Practice
2. Lennert De Smet, Emanuele Sansone, Pedro Dos Martires. Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick. NeurIPS 2023 main track
3. Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan Suykens. Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation. Poster presentation (login to see the poster)
4. Alessio Gravina (University of Pisa), Giulio Lovisotto (Huawei Munich Research Center), Claudio Gallicchio (University of Pisa), Davide Bacciu (University of Pisa), Claas Grohnfeldt (Huawei Munich Research Center). Effective Non-Dissipative Propagation for Continuous-Time Dynamic Graphs. Temporal Graph Learning Workshop @ NeurIPS 2023 (link to the paper)
5. Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin, Alisia Maria Lupidi, Lucie Charlotte Magister, Pietro Lio, Pietro Barbiero. Interpretable Graph Networks Formulate Universal Algebra Conjectures. Main track NeurIPS 2023.
6. Roberto Cipollone, Anders Jonsson, Alessandro Ronca, Mohammad Sadegh Talebi. Provably Efficient Offline Reinforcement Learning in Regular Decision Processes. Poster presentation (details here).
7. Mark Mazumder, Colby Banbury, Xiaozhe Yao, et al. DataPerf: Benchmarks for Data-Centric AI Development. Main track (link to the paper)
8. Taniya Das, Maya Ravichandran, Mark Koch, Nikhil Khatri. GraphRNN Revisited: An Ablation Study and Extensions for Directed Acyclic Graphs. New Frontiers in Graph Learning workshop (link to the paper)
9. Neeratyoy Mallik, Eddie Bergman, Carl Hvarfner, Danny Stoll, Maciej Janowski, Marius Lindauer, Luigi Nardi, Frank Hutter. PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning. Main track (link to the paper)
10. Prabhant Singh, Joaquin Vanschoren (TU Eindhoven). Applications of Optimal Transport Distances in Unsupervised AutoML. Optimal Transport in Machine Learning Workshop (link to the paper)
11. Lorenzo Steccanella, Anders Jonsson. Asymmetric Norms to Approximate the Minimum Action Distance. Workshop on Goal-Conditioned Reinforcement Learning
12. Yushan Zhang Johan Edstedt, Bastian Wandt, Per-Erik Forssen, Maria Magnusson, Michael Felsberg. GMSF: Global Matching Scene Flow. Poster presentation.
13. TU/e group: https://dai.win.tue.nl/highlights/2/
14. Emanuele Marconato, Stefano Teso, Antonio Vergari, Andrea Passerini. Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts. NeurIPS 2023 main track. (link to the paper)