42 citations · 138 across the 17 of their papers we have counts for
18 papers
StarWM: Self-Supervised Trained Attention Routing for Robust World Models
Zeqiang Zhang, Fabian Wurzberger, Maximilian Otte +4
A robust world model must strike the balance between faithfully capturing environmental dynamics and abstracting away from irrelevant content. While reconstruction-based world mode…
Autonomous Learning From Success and Failure: Goal-Conditioned Supervised Learning with Negative Feedback
Zeqiang Zhang, Fabian Wurzberger, Gerrit Schmid +2
Learning from reward functions and imitation learning of demonstrations are the two principal approaches for training autonomous systems that interact with an environment through a…
On the Structure of Information
Sebastian Gottwald, Daniel A. Braun
We characterize information as risk reduction between knowledge states represented by partitions of the underlying probability space. Entropy is risk reduction from no (or partial)…
Automatic Bat Call Classification using Transformer Networks
Frank Fundel, Daniel A. Braun, Sebastian Gottwald
Automatically identifying bat species from their echolocation calls is a difficult but important task for monitoring bats and the ecosystem they live in. Major challenges in automa…
Thermodynamic fluctuation theorems govern human sensorimotor learning
Pedro Hack, Cecilia Lindig-Leon, Sebastian Gottwald +1
The application of thermodynamic reasoning in the study of learning systems has a long tradition. Recently, new tools relating perfect thermodynamic adaptation to the adaptation pr…
Majorization requires infinitely many second laws
Pedro Hack, Daniel A. Braun, Sebastian Gottwald
Majorization is a fundamental model of uncertainty with several applications in areas ranging from thermodynamics to entanglement theory, and constitutes one of the pillars of the…
Countability constraints in order-theoretic approaches to computability
Pedro Hack, Daniel A. Braun, Sebastian Gottwald
Computability on uncountable sets has no standard formalization, unlike that on countable sets, which is given by Turing machines. Some of the approaches to define computability in…
Computation as uncertainty reduction: a simplified order-theoretic framework
Pedro Hack, Daniel A. Braun, Sebastian Gottwald
Although there is a somewhat standard formalization of computability on countable sets given by Turing machines, the same cannot be said about uncountable sets. Among the approache…
The infinite information gap between mathematical and physical representations
Pedro Hack, Daniel A. Braun, Sebastian Gottwald
Partial orders have been used to model several experimental setups, going from classical thermodynamics and general relativity to the quantum realm with its resource theories. In o…
The classification of preordered spaces in terms of monotones: complexity and optimization
Pedro Hack, Daniel A. Braun, Sebastian Gottwald
The study of complexity and optimization in decision theory involves both partial and complete characterizations of preferences over decision spaces in terms of real-valued monoton…
Jarzyski's equality and Crooks' fluctuation theorem for general Markov chains with application to decision-making systems
Pedro Hack, Sebastian Gottwald, Daniel A. Braun
We define common thermodynamic concepts purely within the framework of general Markov chains and derive Jarzynski's equality and Crooks' fluctuation theorem in this setup. In parti…
Representing preorders with injective monotones
Pedro Hack, Daniel A. Braun, Sebastian Gottwald
We introduce a new class of real-valued monotones in preordered spaces, injective monotones. We show that the class of preorders for which they exist lies in between the class of p…
The Two Kinds of Free Energy and the Bayesian Revolution
Sebastian Gottwald, Daniel A. Braun
The concept of free energy has its origins in 19th century thermodynamics, but has recently found its way into the behavioral and neural sciences, where it has been promoted for it…
An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems
Heinke Hihn, Sebastian Gottwald, Daniel A. Braun
Information-theoretic bounded rationality describes utility-optimizing decision-makers whose limited information-processing capabilities are formalized by information constraints.…
Bounded rational decision-making from elementary computations that reduce uncertainty
Sebastian Gottwald, Daniel A. Braun
In its most basic form, decision-making can be viewed as a computational process that progressively eliminates alternatives, thereby reducing uncertainty. Such processes are genera…
Systems of bounded rational agents with information-theoretic constraints
Sebastian Gottwald, Daniel A. Braun
Specialization and hierarchical organization are important features of efficient collaboration in economical, artificial, and biological systems. Here, we investigate the hypothesi…
Bounded Rational Decision-Making with Adaptive Neural Network Priors
Heinke Hihn, Sebastian Gottwald, Daniel A. Braun
Bounded rationality investigates utility-optimizing decision-makers with limited information-processing power. In particular, information theoretic bounded rationality models forma…
Two-term spectral asymptotics for the Dirichlet pseudo-relativistic kinetic energy operator on a bounded domain
Sebastian Gottwald
Continuing the series of works following Weyl's one-term asymptotic formula for the counting function of the eigenvalues of the Dirichlet Laplac…