MFPS 2023 Accepted Papers

The proceedings of both CALCO 2023 and MFPS XXXIX are published!

The list of accepted MFPS papers:

• Sam van Gool, Paul-André Melliès and Vincent Moreau. Profinite lambda-terms and parametricity

• Jean-Simon Pacaud Lemay and Jean-Baptiste Vienney. Graded Differential Categories and Graded Differential Linear Logic

• Dexter Kozen, Alexandra Silva and Erik Voogd. Joint Distributions in Probabilistic Semantics

• Aurore Alcolei, Luc Pellissier and Alexis Saurin. Jumps: the exponential logic of sequentialization

• Samuele Maschio. Implicative models of set theory

• Giorgio Bacci, Radu Mardare, Prakash Panangaden and Gordon Plotkin. Propositional Logics for the Lawvere Quantale

• Larry Moss. Algebra of Self-Expression

• Marcelo Fiore, Zeinab Galal and Farzad Jafarrahmani. Fixpoint constructions in focused orthogonality models of linear logic

• Frederik L. Aagaard, Jonathan Sterling and Lars Birkedal. A denotationally-based program logic for higher-order store

• Bart Jacobs and Dario Stein. Pearl's and Jeffrey's Update as Modes of Learning in Probabilistic Programming

• Fredrik Dahlqvist and Renato Neves. A complete V-equational system for graded lambda-calculus

• Younesse Kaddar and Sam Staton. A model of stochastic memoization and name generation in probabilistic programming: categorical semantics via monads on presheaf categories

• Shin-ya Katsumata, Xavier Rival and Jérémy Dubut. A Categorical Framework for Program Semantics and Semantic Abstraction

• Pietro Sabelli and Maria Emilia Maietti. A topological counterpart of well-founded trees in dependent type theory

• Siva Somayyajula and Frank Pfenning. Dependent Type Refinements for Futures

• Michael Shulman. Semantics of multimodal adjoint type theory

• Jean-Simon Lemay. Cartesian Differential Kleisli Categories

• Frank de Boer, Stijn de Gouw and Hans Dieter Hiep. Dynamic Separation Logic

• Alex Dixon and Andrzej Murawski. Saturating Automata for Game Semantics

• Pietro Di Gianantonio, Abbas Edalat and Ran Gutin. A Language for Evaluating Derivatives of Functionals Using Automatic Differentiation