Zobrazeno 1 - 10
of 192
pro vyhledávání: '"Buckley, Christopher L."'
Recently, 3D Gaussian Splatting has emerged as a promising approach for modeling 3D scenes using mixtures of Gaussians. The predominant optimization method for these models relies on backpropagating gradients through a differentiable rendering pipeli
Externí odkaz:
http://arxiv.org/abs/2410.03592
Although research has produced promising results demonstrating the utility of active inference (AIF) in Markov decision processes (MDPs), there is relatively less work that builds AIF models in the context of environments and problems that take the f
Externí odkaz:
http://arxiv.org/abs/2409.14216
Publikováno v:
4th International Workshop on Active Inference, 2023
Organisms have to keep track of the information in the environment that is relevant for adaptive behaviour. Transmitting information in an economical and efficient way becomes crucial for limited-resourced agents living in high-dimensional environmen
Externí odkaz:
http://arxiv.org/abs/2409.08892
An open problem in artificial intelligence is how systems can flexibly learn discrete abstractions that are useful for solving inherently continuous problems. Previous work in computational neuroscience has considered this functional integration of d
Externí odkaz:
http://arxiv.org/abs/2409.01066
Predictive coding (PC) is an energy-based learning algorithm that performs iterative inference over network activities before updating weights. Recent work suggests that PC can converge in fewer learning steps than backpropagation thanks to its infer
Externí odkaz:
http://arxiv.org/abs/2408.11979
An open problem in artificial intelligence is how systems can flexibly learn discrete abstractions that are useful for solving inherently continuous problems. Previous work has demonstrated that a class of hybrid state-space model known as recurrent
Externí odkaz:
http://arxiv.org/abs/2408.10970
Autor:
Friston, Karl J., Salvatori, Tommaso, Isomura, Takuya, Tschantz, Alexander, Kiefer, Alex, Verbelen, Tim, Koudahl, Magnus, Paul, Aswin, Parr, Thomas, Razi, Adeel, Kagan, Brett, Buckley, Christopher L., Ramstead, Maxwell J. D.
Recent advances in theoretical biology suggest that basal cognition and sentient behaviour are emergent properties of in vitro cell cultures and neuronal networks, respectively. Such neuronal networks spontaneously learn structured behaviours in the
Externí odkaz:
http://arxiv.org/abs/2312.07547
Autor:
Friston, Karl J., Da Costa, Lancelot, Tschantz, Alexander, Kiefer, Alex, Salvatori, Tommaso, Neacsu, Victorita, Koudahl, Magnus, Heins, Conor, Sajid, Noor, Markovic, Dimitrije, Parr, Thomas, Verbelen, Tim, Buckley, Christopher L
This paper concerns structure learning or discovery of discrete generative models. It focuses on Bayesian model selection and the assimilation of training data or content, with a special emphasis on the order in which data are ingested. A key move -
Externí odkaz:
http://arxiv.org/abs/2311.10300
The ability to invent new tools has been identified as an important facet of our ability as a species to problem solve in dynamic and novel environments. While the use of tools by artificial agents presents a challenging task and has been widely iden
Externí odkaz:
http://arxiv.org/abs/2311.03893