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AI Blogs
Evaluating Instrument Validity using the Principle of Independent Mechanisms Patrick F. Burauel; 24(176):1−56, 2023. Abstract The validity of instrumental variables for estimating causal effects is often controversial and typically justified through narratives. However, assessing critical assumptions can be challenging due…
arXivLabs is a platform that enables collaborators to create and share new features for arXiv directly on our website. Both individuals and organizations that collaborate with arXivLabs share our core values of openness, community, excellence, and user data privacy. We…
Fitting Autoregressive Graph Generative Models through Maximum Likelihood Estimation Xu Han, Xiaohui Chen, Francisco J. R. Ruiz, Li-Ping Liu; 24(97):1−30, 2023. Abstract The objective of this study is to address the problem of fitting autoregressive graph generative models using maximum…
[Submitted on 31 Aug 2023] Click here to download a PDF of the paper titled “On a Connection between Differential Games, Optimal Control, and Energy-based Models for Multi-Agent Interactions” by Christopher Diehl, Tobias Klosek, Martin Krüger, Nils Murzyn, and Torsten…
Evaluation of Algorithm Portfolios using Item Response Theory Authors: Sevvandi Kandanaarachchi, Kate Smith-Miles; Published in Journal of Machine Learning Research, Volume 24, Issue 177, 2023. Abstract Item Response Theory (IRT) is a method used in Educational Psychometrics to evaluate student…
Score-based and diffusion models have become popular in generating both conditional and unconditional content. However, conditional generation typically requires training a conditional model or utilizing classifier guidance, even when a classifier for uncorrupted data is available. In this study, we…
Connectivity Matters: Neural Network Pruning Through the Lens of Effective Sparsity Artem Vysogorets, Julia Kempe; 24(99):1−23, 2023. Abstract Neural network pruning is an area of research that has gained significant interest, particularly in high sparsity regimes. In this field, accurate…
In order to enable effective manipulation of objects by robots in real-world settings, accurate estimation of their 6D pose is crucial. However, many current approaches struggle to make accurate predictions when faced with new instances of objects and heavy occlusions.…
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning Wenhao Li, Bo Jin, Xiangfeng Wang, Junchi Yan, Hongyuan Zha; 24(178):1−75, 2023. Abstract Traditional centralized multi-agent reinforcement learning (MARL) algorithms are sometimes impractical in complex applications due to lack of…
The limitations of graph neural networks (GNNs) are often caused by over-squashing and over-smoothing. Over-smoothing erases node differences, while over-squashing hinders information propagation over long distances. These issues stem from the graph structure itself. To address these problems in graph…
