English
Related papers

Related papers: A framework for characterizing covariational reaso…

200 papers

Language is contextual as meanings of words are dependent on their contexts. Contextuality is, concomitantly, a well-defined concept in quantum mechanics where it is considered a major resource for quantum computations. We investigate…

Computation and Language · Computer Science 2021-08-02 Daphne Wang , Mehrnoosh Sadrzadeh , Samson Abramsky , Victor H. Cervantes

Models of a phenomenon are often developed by examining it under different experimental conditions, or measurement contexts. The resultant probabilistic models assume that the underlying random variables, which define a measurable set of…

Artificial Intelligence · Computer Science 2018-02-05 Peter D. Bruza

Recent developments in reasoning capabilities have enabled large language models to solve increasingly complex mathematical, symbolic, and logical tasks. Interestingly, while reasoning models are often trained to generate monolingual text,…

Computation and Language · Computer Science 2026-04-20 Eleanor M. Lin , David Jurgens

Developing expertise in physics requires appropriate integration and assimilation of physics and mathematics. Instructors and students often describe physics courses in terms of their emphasis on conceptual and quantitative problem-solving.…

Physics Education · Physics 2025-12-11 Apekshya Ghimire , Chandralekha Singh

A common learning goal for modern physics instructors is for students to recognize a difference between the experimental uncertainty of classical physics and the fundamental uncertainty of quantum mechanics. Our studies suggest this…

Physics Education · Physics 2011-09-08 Charles Baily

We focus on three distinct lines of recent developments: edge modes and boundary charges in gravitational physics, relational dynamics in classical and quantum gravity, and quantum reference frames. We argue that these research directions…

History and Philosophy of Physics · Physics 2025-02-03 Henrique Gomes , Simon Langenscheidt , Daniele Oriti

There exist well-developed frameworks for causal modelling, but these require rather a lot of human domain expertise to define causal variables and perform interventions. In order to enable autonomous agents to learn abstract causal models…

Artificial Intelligence · Computer Science 2022-08-15 Taco Cohen

The rapid advancement of embodied intelligence and world models has intensified efforts to integrate physical laws into AI systems, yet physical perception and symbolic physics reasoning have developed along separate trajectories without a…

This paper re-centres the discussion of student learning in physics to focus on context. In order to do so, a theoretically-motivated understanding of context is developed. Given a well-defined notion of context, data from a novel…

Physics Education · Physics 2009-11-11 N. D. Finkelstein

The modeling theory of instruction is widely applied and highly successful in high-school instruction, and seldom in university physics. One reason is lack of familiarity with models in the physics classroom. Ongoing curriculum development…

Physics Education · Physics 2007-05-23 Eric Brewe

Several concrete examples in quantum information are discussed to demonstrate the importance of proper modeling that relates the mathematical description to real-world applications. In particular, it is shown that some commonly accepted…

Quantum Physics · Physics 2007-05-23 Horace P. Yuen

I offer an account of how the quantum theory we have helps us explain so much. The account depends on a pragmatist interpretation of the theory: This takes a quantum state to serve solely as a source of sound advice to physically situated…

History and Philosophy of Physics · Physics 2016-01-06 Richard Healey

Most introductory quantum physics instructors would agree that transitioning students from classical to quantum thinking is an important learning goal, but may disagree on whether or how this can be accomplished. Although (and perhaps…

Physics Education · Physics 2015-10-28 Charles Baily , Noah D. Finkelstein

Estimating an individual's counterfactual outcomes under interventions is a challenging task for traditional causal inference and supervised learning approaches when the outcome is high-dimensional (e.g. gene expressions, facial images) and…

Machine Learning · Computer Science 2025-03-19 Yulun Wu , Louie McConnell , Claudia Iriondo

We characterize the class of quantum measurements that matches the applications of quantum theory to cognition (and decision making) - quantum-like modeling. Projective measurements describe the canonical measurements of the basic…

Artificial Intelligence · Computer Science 2025-12-15 Miho Fuyama , Andrei Khrennikov , Masanao Ozawa

Research in cognitive science has provided extensive evidence of human cognitive ability in performing physical reasoning of objects from noisy perceptual inputs. Such a cognitive ability is commonly known as intuitive physics. With…

Machine Learning · Computer Science 2022-04-29 Jiafei Duan , Arijit Dasgupta , Jason Fischer , Cheston Tan

We present a novel task that measures how people generalize objects' causal powers based on observing a single (Experiment 1) or a few (Experiment 2) causal interactions between object pairs. We propose a computational modeling framework…

Artificial Intelligence · Computer Science 2021-11-25 Bonan Zhao , Christopher G. Lucas , Neil R. Bramley

One of the most basic notions in physics is the partitioning of a system into subsystems, and the study of correlations among its parts. In this work, we explore these notions in the context of quantum reference frame (QRF) covariance, in…

The gap between classical mechanics and quantum mechanics has an important interpretive implication: the Universe must have an irreducible fundamental level, which determines the properties of matter at higher levels of organization. We…

Quantum Physics · Physics 2007-05-23 G. N. Mardari

Causality has the potential to truly transform the way we solve a large number of real-world problems. Yet, so far, its potential largely remains to be unlocked as causality often requires crucial assumptions which cannot be tested in…

Machine Learning · Computer Science 2024-02-15 Jeroen Berrevoets , Krzysztof Kacprzyk , Zhaozhi Qian , Mihaela van der Schaar
‹ Prev 1 4 5 6 7 8 10 Next ›