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We propose a new Bayesian Neural Net formulation that affords variational inference for which the evidence lower bound is analytically tractable subject to a tight approximation. We achieve this tractability by (i) decomposing ReLU…

Machine Learning · Statistics 2019-06-13 Manuel Haussmann , Fred A. Hamprecht , Melih Kandemir

Previous work has shown that reasoning with real-time temporal logics is often simpler when restricted to models with bounded variability---where no more than v events may occur every V time units, for given v, V. When reasoning about…

Logic in Computer Science · Computer Science 2015-02-24 Carlo A. Furia , Paola Spoletini

This paper shows how to derive nested calculi from labelled calculi for propositional intuitionistic logic and first-order intuitionistic logic with constant domains, thus connecting the general results for labelled calculi with the more…

Logic in Computer Science · Computer Science 2020-02-04 Tim Lyon

The instrumental variables (IVs) method is a leading empirical strategy for causal inference. Finding IVs is a heuristic and creative process, and justifying its validity -- especially exclusion restrictions -- is largely rhetorical. We…

Econometrics · Economics 2025-06-06 Sukjin Han

We consider the problem of exact probabilistic inference for Union of Conjunctive Queries (UCQs) on tuple-independent databases. For this problem, two approaches currently coexist. In the extensional method, query evaluation is performed by…

Databases · Computer Science 2021-04-29 Mikaël Monet

This article presents modal versions of resource-conscious logics. We concentrate on extensions of variants of Linear Logic with one minimal non-normal modality. In earlier work, where we investigated agency in multi-agent systems, we have…

Logic in Computer Science · Computer Science 2015-09-07 Daniele Porello , Nicolas Troquard

Differentiable inductive logic programming (ILP) techniques have proven effective at finding approximate rule-based solutions to link prediction and node classification problems on knowledge graphs; however, the common assumption of…

Artificial Intelligence · Computer Science 2025-08-12 Blair Johnson , Clayton Kerce , Faramarz Fekri

We introduce a deterministic variational formulation for training Bayesian last layer neural networks. This yields a sampling-free, single-pass model and loss that effectively improves uncertainty estimation. Our variational Bayesian last…

Machine Learning · Computer Science 2024-04-18 James Harrison , John Willes , Jasper Snoek

Sequential recommendation (SR) leverages users' dynamic preferences, with recent advances incorporating multi-interest learning to model diverse user interests. However, most multi-interest SR models rely on noisy, sparse implicit feedback,…

Information Retrieval · Computer Science 2025-05-08 Shutong Qiao , Chen Gao , Wei Yuan , Yong Li , Hongzhi Yin

We introduce EVIL (\textbf{EV}olving \textbf{I}nterpretable algorithms with \textbf{L}LMs), an approach that uses LLM-guided evolutionary search to discover simple, interpretable algorithms for dynamical systems inference. Rather than…

Machine Learning · Computer Science 2026-04-20 David Berghaus

In sequent calculi, cut elimination is a property that guarantees that any provable formula can be proven analytically. For example, Gentzen's classical and intuitionistic calculi LK and LJ enjoy cut elimination. The property is less…

Logic in Computer Science · Computer Science 2020-08-11 Ekaterina Komendantskaya , Dmitry Rozplokhas , Henning Basold

Dynamic logic is a modal logic for reasoning about programs. A cyclic proof system is a proof system that allows proofs containing cycles and is an alternative to a proof system containing (co-)induction. This paper introduces a sequent…

Logic in Computer Science · Computer Science 2026-03-03 Yukihiro Oda

In this paper we present a formalization of Intuitionistic Propositional Logic in the Lean proof assistant. Our approach focuses on verifying two completeness proofs for the studied logical system, as well as exploring the relation between…

Logic in Computer Science · Computer Science 2024-11-01 Dafina Trufaş

Cut-elimination is the bedrock of proof theory. It is the algorithm that eliminates cuts from a sequent calculus proof that leads to cut-free calculi and applications. Cut-elimination applies to many logics irrespective of their semantics.…

Logic in Computer Science · Computer Science 2022-03-04 Agata Ciabattoni , Timo Lang , Revantha Ramanayake

Deep latent variable models (DLVMs) combine the approximation abilities of deep neural networks and the statistical foundations of generative models. Variational methods are commonly used for inference; however, the exact likelihood of…

Machine Learning · Statistics 2018-06-29 Pierre-Alexandre Mattei , Jes Frellsen

The vast quantity of data generated and captured every day has led to a pressing need for tools and processes to organize, analyze and interrelate this data. Automated reasoning and optimization tools with inherent support for data could…

Logic in Computer Science · Computer Science 2014-09-16 Panagiotis Manolios , Vasilis Papavasileiou , Mirek Riedewald

In this paper, we propose a relational semantics of propositional language, which unifies the relational semantics of intuitionistic logic, Visser's Basic Propositional Logic and orthologic. Working in language $\{\bot,\land,\neg\}$ and…

Logic · Mathematics 2024-12-13 Zhicheng Chen

Cumulative logics are studied in an abstract setting, i.e., without connectives, very much in the spirit of Makinson's early work. A powerful representation theorem characterizes those logics by choice functions that satisfy a weakening of…

Artificial Intelligence · Computer Science 2007-05-23 Daniel Lehmann

The purpose of this paper is to introduce a bi-intuitionistic sequent calculus and to give proofs of admissibility for its structural rules. The calculus I will present, called SC2Int, is a sequent calculus for the bi-intuitionistic logic…

Logic in Computer Science · Computer Science 2020-10-01 Sara Ayhan

We present Innovator-VL, a scientific multimodal large language model designed to advance understanding and reasoning across diverse scientific domains while maintaining excellent performance on general vision tasks. Contrary to the trend…