Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
- Vijay E
- Arindam Jati
- et al.
- 2024
- NeurIPS 2024
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- NeurIPS 2024
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Interventional Causal Discovery in a Mixture of DAGs
- Burak Varici
- Dmitriy Katz-Rogozhnikov
- et al.
- 2024
- NeurIPS 2024
Distributional Preference Alignment of LLMs via Optimal Transport
- Igor Melnyk
- Youssef Mroueh
- et al.
- 2024
- NeurIPS 2024
Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking
- Gabriel Rioux
- Apoorva Nitsure
- et al.
- 2024
- NeurIPS 2024
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models
- Jinghan Jia
- Jiancheng Liu
- et al.
- 2024
- NeurIPS 2024
Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series
- Giangiacomo Mercatali
- Andre Freitas
- et al.
- 2024
- NeurIPS 2024
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery
- Yue Yu
- Ning Liu
- et al.
- 2024
- NeurIPS 2024
Interpolating Item and User Fairness in Multi-Sided Recommendations
- Qinyi Chen
- Jason Cheuk Nam Liang
- et al.
- 2024
- NeurIPS 2024
Multi-Scale Representation Learning for Protein Fitness Prediction
- Zuobai Zhang
- Pascal Notin
- et al.
- 2024
- NeurIPS 2024
Limits of Transformer Language Models on Learning to Compose Algorithms
- Jonathan Thomm
- Aleksandar Terzic
- et al.
- 2024
- NeurIPS 2024