2024 "probabilistic modeling" Papers
12 papers found
Accelerating the Global Aggregation of Local Explanations
Alon Mor, Yonatan Belinkov, Benny Kimelfeld
AAAI 2024paperarXiv:2312.07991
6
citations
A Probabilistic Approach to Learning the Degree of Equivariance in Steerable CNNs
Lars Veefkind, Gabriele Cesa
ICML 2024posterarXiv:2406.03946
Arrows of Time for Large Language Models
Vassilis Papadopoulos, Jérémie Wenger, Clement Hongler
ICML 2024posterarXiv:2401.17505
Beyond the Norms: Detecting Prediction Errors in Regression Models
Andres Altieri, Marco Romanelli, Georg Pichler et al.
ICML 2024spotlightarXiv:2406.06968
CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling
JUNCHAO GONG, LEI BAI, Peng Ye et al.
ICML 2024posterarXiv:2402.04290
CLIFF: Continual Latent Diffusion for Open-Vocabulary Object Detection
Wuyang Li, Xinyu Liu, Jiayi Ma et al.
ECCV 2024poster
14
citations
Domain Invariant Learning for Gaussian Processes and Bayesian Exploration
Xilong Zhao, Siyuan Bian, Yaoyun Zhang et al.
AAAI 2024paperarXiv:2312.11318
2
citations
Dual Operating Modes of In-Context Learning
Ziqian Lin, Kangwook Lee
ICML 2024posterarXiv:2402.18819
Probabilistic Modeling of Interpersonal Coordination Processes
Paulo Soares, Adarsh Pyarelal, Meghavarshini Krishnaswamy et al.
ICML 2024oral
RICA^2: Rubric-Informed, Calibrated Assessment of Actions
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV et al.
ECCV 2024poster
12
citations
SimPro: A Simple Probabilistic Framework Towards Realistic Long-Tailed Semi-Supervised Learning
Chaoqun Du, Yizeng Han, Gao Huang
ICML 2024posterarXiv:2402.13505
Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding
Guangyi Liu, Yu Wang, Zeyu Feng et al.
ICML 2024posterarXiv:2402.19009