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Related papers: Geometry of Program Synthesis

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With the surge of multi- and manycores, much research has focused on algorithms for mapping and scheduling on these complex platforms. Large classes of these algorithms face scalability problems. This is why diverse methods are commonly…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-07-27 Andrés Goens , Sergio Siccha , Jeronimo Castrillon

Significant strides have been made toward designing better generative models in recent years. Despite this progress, however, state-of-the-art approaches are still largely unable to capture complex global structure in data. For example,…

Machine Learning · Computer Science 2019-01-25 Halley Young , Osbert Bastani , Mayur Naik

In this paper, we study quantitative properties of quantum programs. Properties of interest include (positive) almost-sure termination, expected runtime or expected cost, that is, for example, the expected number of applications of a given…

Logic in Computer Science · Computer Science 2023-12-22 Martin Avanzini , Georg Moser , Romain Péchoux , Simon Perdrix

Universality is a key hypothesis in mechanistic interpretability -- that different models learn similar features and circuits when trained on similar tasks. In this work, we study the universality hypothesis by examining how small neural…

Machine Learning · Computer Science 2023-05-26 Bilal Chughtai , Lawrence Chan , Neel Nanda

We present a new domain-agnostic synthesis technique for generating programs from input-output examples. Our method, called metric program synthesis, relaxes the well-known observational equivalence idea (used widely in bottom-up…

Programming Languages · Computer Science 2022-10-12 John Feser , Isil Dillig , Armando Solar-Lezama

We analyze the problem of global reconstruction of functions as accurately as possible, based on partial information in the form of a truncated power series at some point, and additional analyticity properties. This situation occurs…

Complex Variables · Mathematics 2022-05-30 Ovidiu Costin , Gerald V. Dunne

We propose a novel framework of program and invariant synthesis called neural network-guided synthesis. We first show that, by suitably designing and training neural networks, we can extract logical formulas over integers from the weights…

Programming Languages · Computer Science 2021-08-26 Naoki Kobayashi , Taro Sekiyama , Issei Sato , Hiroshi Unno

For a given target system and apparatus described by quantum theory, the so-called quantum no-programming theorem indicates that a family of states called programs in the apparatus with a fixed unitary operation on the total system programs…

Quantum Physics · Physics 2023-04-05 Takayuki Miyadera , Ryo Takakura

Designing a static analysis is generally a substantial undertaking, requiring significant expertise in both program analysis and the domain of the program analysis, and significant development resources. As a result, most program analyses…

Programming Languages · Computer Science 2018-10-17 Colin S. Gordon

While concepts and tools from Theoretical Computer Science are regularly applied to, and significantly support, software development for discrete problems, Numerical Engineering largely employs recipes and methods whose correctness and…

Computational Complexity · Computer Science 2018-01-23 Akitoshi Kawamura , Martin Ziegler

The abundance of publicly available source code repositories, in conjunction with the advances in neural networks, has enabled data-driven approaches to program analysis. These approaches, called neural program analyzers, use neural…

Software Engineering · Computer Science 2022-07-12 Md Rafiqul Islam Rabin , Mohammad Amin Alipour

In this paper, we identify a fragment of second-order logic with restricted quantification that is expressive enough to capture numerous static analysis problems (e.g. safety proving, bug finding, termination and non-termination proving,…

Logic in Computer Science · Computer Science 2015-09-01 Cristina David , Daniel Kroening , Matt Lewis

This report outlines an approach to learning generative models from data. We express models as probabilistic programs, which allows us to capture abstract patterns within the examples. By choosing our language for programs to be an…

Artificial Intelligence · Computer Science 2011-10-27 Irvin Hwang , Andreas Stuhlmüller , Noah D. Goodman

We propose a novel method for automatic program synthesis. P-Tree Programming represents the program search space through a single probabilistic prototype tree. From this prototype tree we form program instances which we evaluate on a given…

Artificial Intelligence · Computer Science 2017-07-13 Christian Oesch

Quantum Computing is a new paradigm that enables several advances which are impossible using classical technology. With the rise of quantum computers, the software is also invited to change so that it can better fit this new computation…

Software Engineering · Computer Science 2024-03-19 Paulo Eduardo Zanni Junior , Valter Vieira de Camargo

Decomposition, statically dividing a program into multiple units, is a common programming technique for realizing parallelism and refining programs. The decomposition of a sequential program into components is tedious, due to the…

Software Engineering · Computer Science 2020-09-09 Sabah Al-Fedaghi

Quantum computers promise to transform our notions of computation by offering a completely new paradigm. To achieve scalable quantum computation, optimizing compilers and a corresponding software design flow will be essential. We present a…

Programming Languages · Computer Science 2018-07-24 Thomas Häner , Damian S. Steiger , Krysta Svore , Matthias Troyer

Program synthesis and repair have emerged as an exciting area of research, driven by the potential for revolutionary advances in programmer productivity. Among most promising ideas emerging for synthesis are syntax-driven search,…

Programming Languages · Computer Science 2017-07-14 Manos Koukoutos , Mukund Raghothaman , Etienne Kneuss , Viktor Kuncak

Automatic software generation based on some specification is known as program synthesis. Most existing approaches formulate program synthesis as a search problem with discrete parameters. In this paper, we present a novel formulation of…

Artificial Intelligence · Computer Science 2023-04-04 Shantanu Mandal , Todd A. Anderson , Javier Turek , Justin Gottschlich , Abdullah Muzahid

We discuss various universality aspects of numerical computations using standard algorithms. These aspects include empirical observations and rigorous results. We also make various speculations about computation in a broader sense.

Probability · Mathematics 2017-03-24 Percy Deift , Thomas Trogdon