Zobrazeno 1 - 10
of 859
pro vyhledávání: '"Tschantz, A."'
Autor:
Heins, Conor, Wu, Hao, Markovic, Dimitrije, Tschantz, Alexander, Beck, Jeff, Buckley, Christopher
Balancing computational efficiency with robust predictive performance is crucial in supervised learning, especially for critical applications. Standard deep learning models, while accurate and scalable, often lack probabilistic features like calibrat
Externí odkaz:
http://arxiv.org/abs/2408.16429
Autor:
Friston, Karl, Heins, Conor, Verbelen, Tim, Da Costa, Lancelot, Salvatori, Tommaso, Markovic, Dimitrije, Tschantz, Alexander, Koudahl, Magnus, Buckley, Christopher, Parr, Thomas
This paper describes a discrete state-space model -- and accompanying methods -- for generative modelling. This model generalises partially observed Markov decision processes to include paths as latent variables, rendering it suitable for active infe
Externí odkaz:
http://arxiv.org/abs/2407.20292
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
Autor:
Kohli, Nitin, Tschantz, Michael Carl
We use decision theory to compare variants of differential privacy from the perspective of prospective study participants. We posit the existence of a preference ordering on the set of potential consequences that study participants can incur, which e
Externí odkaz:
http://arxiv.org/abs/2310.06258
Autor:
Friston, Karl J, Ramstead, Maxwell J D, Kiefer, Alex B, Tschantz, Alexander, Buckley, Christopher L, Albarracin, Mahault, Pitliya, Riddhi J, Heins, Conor, Klein, Brennan, Millidge, Beren, Sakthivadivel, Dalton A R, Smithe, Toby St Clere, Koudahl, Magnus, Tremblay, Safae Essafi, Petersen, Capm, Fung, Kaiser, Fox, Jason G, Swanson, Steven, Mapes, Dan, René, Gabriel
Publikováno v:
Collective Intelligence, 3(1), 2024
This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond). Its denouement is a cyber-physical ecosystem of natural and synthetic sense-making, in which humans are integral
Externí odkaz:
http://arxiv.org/abs/2212.01354
Capsule networks are a neural network architecture specialized for visual scene recognition. Features and pose information are extracted from a scene and then dynamically routed through a hierarchy of vector-valued nodes called 'capsules' to create a
Externí odkaz:
http://arxiv.org/abs/2209.02567
Autor:
Tschantz, Michael Carl
The near universal condemnation of proxy discrimination hides a disagreement over what it is. This work surveys various notions of proxy and proxy discrimination found in prior work and represents them in a common framework. These notions variously t
Externí odkaz:
http://arxiv.org/abs/2205.05265
Predictive coding is an influential model of cortical neural activity. It proposes that perceptual beliefs are furnished by sequentially minimising "prediction errors" - the differences between predicted and observed data. Implicit in this proposal i
Externí odkaz:
http://arxiv.org/abs/2204.02169
Bruineberg and colleagues helpfully distinguish between instrumental and ontological interpretations of Markov blankets, exposing the dangers of using the former to make claims about the latter. However, proposing a sharp distinction neglects the val
Externí odkaz:
http://arxiv.org/abs/2201.06900