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Intrinsic Associative Memory on Riemannian Manifolds: Curvature, Capacity, and Emergent Modes
Krishnakumar Balasubramanian, Zhaoyang Shi
Geometry does more than constrain an associative memory: curvature determines what it remembers and which states it creates. We develop intrinsic dense associative memories on Riem…
Graph Memory: Spectral Associative Memory via Dirichlet Energy
Zhaoyang Shi
Dense associative memories have traditionally focused on storing and retrieving vector-valued patterns. Many modern machine learning problems, however, are naturally graph-structur…
Dense Associative Memory with Epanechnikov Energy
Benjamin Hoover, Zhaoyang Shi, Krishnakumar Balasubramanian +2
We propose a novel energy function for Dense Associative Memory (DenseAM) networks, the log-sum-ReLU (LSR), inspired by optimal kernel density estimation. Unlike the common log-sum…
LOD: Latent Objective Discovery in Heterogeneous Multi-Agent Reinforcement Learning
Ke Sun, Zhaoyang Shi
In multi-agent reinforcement learning (MARL) settings, agents are often heterogeneous with diverse intrinsic utility functions. In this study, we introduce Latent Objective Discove…