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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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
LLM-Pilot: Characterize and Optimize Performance of your LLM Inference Services
- Gosia Lazuka
- Andreea Simona Anghel
- et al.
- 2024
- SC 2024
How do Categorical Duplicates Affect ML? A New Benchmark and Empirical Analyses
- Vraj Shah
- Thomas Parashos
- et al.
- 2024
- VLDB 2024
What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks
- Irene Ko
- Pin-Yu Chen
- et al.
- 2024
- ICML 2024
Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory
- Kai Xu
- Hong Ge
- 2024
- ICML 2024
Unraveling the Key Components of OOD Generalization via Diversification
- Harold Benoit
- Liangze Jiang
- et al.
- 2024
- ICLR 2024
Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors
- Ido Amos
- Jonathan Berant
- et al.
- 2024
- ICLR 2024