inductive bia

Less Is More: Label Recommendation for Weakly Supervised Point Cloud Semantic Segmentation AAAI 2024 Leveraging Partial Symmetry for Multi-Agent Reinforcement Learning AAAI 2024 Multi-Dimensional Hyena for Spatial Inductive Bias AISTATS 2024 Neural Redshift: Random Networks are not Random Functions CVPR 2024 On Efficiently Representing Regular Languages as RNNs ACL 2024 On the Inductive Biases of Demographic Parity-based Fair Learning Algorithms UAI 2024 On the Inductive Bias of Stacking Towards Improving Reasoning NeurIPS 2024 Orbit-Equivariant Graph Neural Networks ICLR 2024 Physics-Informed Regularization for Domain-Agnostic Dynamical System Modeling NeurIPS 2024 Probing the Decision Boundaries of In-context Learning in Large Language Models NeurIPS 2024 Rethinking Inductive Biases for Surface Normal Estimation CVPR 2024 SIP: Injecting a Structural Inductive Bias into a Seq2Seq Model by Simulation ACL 2024 Strengthening Structural Inductive Biases by Pre-training to Perform Syntactic Transformations EMNLP 2024 Symmetric Basis Convolutions for Learning Lagrangian Fluid Mechanics ICLR 2024 The Role of Learning Algorithms in Collective Action ICML 2024 Towards Exact Computation of Inductive Bias IJCAI 2024 Towards Understanding Inductive Bias in Transformers: A View From Infinity ICML 2024 Towards Understanding the Relationship between In-context Learning and Compositional Generalization COLING 2024 Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure NeurIPS 2024 Understanding Visual Feature Reliance through the Lens of Complexity NeurIPS 2024 Unitary Convolutions for Learning on Graphs and Groups NeurIPS 2024 Unveiling Divergent Inductive Biases of LLMs on Temporal Data NAACL 2024 Viewing Transformers Through the Lens of Long Convolutions Layers ICML 2024 Why are Sensitive Functions Hard for Transformers? ACL 2024 XB-MAML: Learning Expandable Basis Parameters for Effective Meta-Learning with Wide Task Coverage AISTATS 2024