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pro vyhledávání: '"A. A. Krotov"'
Autor:
A. A. Krotov
Publikováno v:
Концепт: философия, религия, культура, Vol 8, Iss 1, Pp 7-24 (2024)
The subject of the study is the dispute between the Russian philosopher, K. Leontiev, and the French emperor, Napoleon III, regarding the meaning and orientation of historical events. The topicality of the study is determined by the importance of the
Externí odkaz:
https://doaj.org/article/2137d71d38a2436b8984a975a2c8d216
Autor:
Goryainov, Sergey, Krotov, Denis
In Cayley graphs on the additive group of a small vector space over GF$(q)$, $q=2,3$, we look for completely regular (CR) codes whose parameters are new in Hamming graphs over the same field. The existence of a CR code in such Cayley graph $G$ implie
Externí odkaz:
http://arxiv.org/abs/2411.09698
Dense Associative Memories are high storage capacity variants of the Hopfield networks that are capable of storing a large number of memory patterns in the weights of the network of a given size. Their common formulations typically require storing ea
Externí odkaz:
http://arxiv.org/abs/2410.24153
Autor:
Achilli, Beatrice, Ventura, Enrico, Silvestri, Gianluigi, Pham, Bao, Raya, Gabriel, Krotov, Dmitry, Lucibello, Carlo, Ambrogioni, Luca
Generative diffusion processes are state-of-the-art machine learning models deeply connected with fundamental concepts in statistical physics. Depending on the dataset size and the capacity of the network, their behavior is known to transition from a
Externí odkaz:
http://arxiv.org/abs/2410.08727
We define a triangle design as a partition of the set of $2$-dimensional subspaces of an $n$-dimensional vector space into triangles, where a triangle consists of three subspaces with the trivial, $0$-dimensional, intersection and $1$-dimensional mut
Externí odkaz:
http://arxiv.org/abs/2407.19157
Large Language Models (LLMs) struggle to handle long input sequences due to high memory and runtime costs. Memory-augmented models have emerged as a promising solution to this problem, but current methods are hindered by limited memory capacity and r
Externí odkaz:
http://arxiv.org/abs/2402.13449
Astrocytes, the most abundant type of glial cell, play a fundamental role in memory. Despite most hippocampal synapses being contacted by an astrocyte, there are no current theories that explain how neurons, synapses, and astrocytes might collectivel
Externí odkaz:
http://arxiv.org/abs/2311.08135
Autor:
Hoover, Benjamin, Strobelt, Hendrik, Krotov, Dmitry, Hoffman, Judy, Kira, Zsolt, Chau, Duen Horng
The generative process of Diffusion Models (DMs) has recently set state-of-the-art on many AI generation benchmarks. Though the generative process is traditionally understood as an "iterative denoiser", there is no universally accepted language to de
Externí odkaz:
http://arxiv.org/abs/2309.16750
Publikováno v:
Advances in Neural Information Processing Systems 36 (2023)
Sequence memory is an essential attribute of natural and artificial intelligence that enables agents to encode, store, and retrieve complex sequences of stimuli and actions. Computational models of sequence memory have been proposed where recurrent H
Externí odkaz:
http://arxiv.org/abs/2306.04532
Clustering is a widely used unsupervised learning technique involving an intensive discrete optimization problem. Associative Memory models or AMs are differentiable neural networks defining a recursive dynamical system, which have been integrated wi
Externí odkaz:
http://arxiv.org/abs/2306.03209