Programs as Singularities
Fuente:
arXiv
Saved in:
| Main Authors: | Murfet, Daniel, Troiani, Will |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Linear Logic and the Hilbert Scheme
by: Troiani, William, et al.
Published: (2025)
by: Troiani, William, et al.
Published: (2025)
Linear Logic and Quantum Error Correcting Codes
by: Murfet, Daniel, et al.
Published: (2024)
by: Murfet, Daniel, et al.
Published: (2024)
Logical GANs: Adversarial Learning through Ehrenfeucht Fraisse Games
by: Mannucci, Mirco A.
Published: (2025)
by: Mannucci, Mirco A.
Published: (2025)
From learnable objects to learnable random objects
by: Anderson, Aaron, et al.
Published: (2025)
by: Anderson, Aaron, et al.
Published: (2025)
How (and when) can you fit examples to logic-based hypothesis classes over infinite structures?
by: Benedikt, Michael, et al.
Published: (2026)
by: Benedikt, Michael, et al.
Published: (2026)
LLASP: Fine-tuning Large Language Models for Answer Set Programming
by: Coppolillo, Erica, et al.
Published: (2024)
by: Coppolillo, Erica, et al.
Published: (2024)
Neural Model Checking
by: Giacobbe, Mirco, et al.
Published: (2024)
by: Giacobbe, Mirco, et al.
Published: (2024)
The unstable formula theorem revisited via algorithms
by: Malliaris, Maryanthe, et al.
Published: (2022)
by: Malliaris, Maryanthe, et al.
Published: (2022)
Agnostic Online Learning and Excellent Sets
by: Malliaris, Maryanthe, et al.
Published: (2021)
by: Malliaris, Maryanthe, et al.
Published: (2021)
Value Functions as Supermartingale Certificates
by: Abate, Alessandro, et al.
Published: (2026)
by: Abate, Alessandro, et al.
Published: (2026)
Proof Minimization in Neural Network Verification
by: Isac, Omri, et al.
Published: (2025)
by: Isac, Omri, et al.
Published: (2025)
Space Explanations of Neural Network Classification
by: Labbaf, Faezeh, et al.
Published: (2025)
by: Labbaf, Faezeh, et al.
Published: (2025)
Formalized Hopfield Networks and Boltzmann Machines
by: Cipollina, Matteo, et al.
Published: (2025)
by: Cipollina, Matteo, et al.
Published: (2025)
A General Framework for Property-Driven Machine Learning
by: Flinkow, Thomas, et al.
Published: (2025)
by: Flinkow, Thomas, et al.
Published: (2025)
Lecture Notes on Verifying Graph Neural Networks
by: Schwarzentruber, François
Published: (2025)
by: Schwarzentruber, François
Published: (2025)
Symbolic Snapshot Ensembles
by: Liu, Mingyue, et al.
Published: (2025)
by: Liu, Mingyue, et al.
Published: (2025)
PICID: Proof-Driven Clause Learning in Neural Network Verification
by: Isac, Omri, et al.
Published: (2025)
by: Isac, Omri, et al.
Published: (2025)
A First-Order Logic-Based Alternative to Reward Models in RLHF
by: Jian, Chunjin, et al.
Published: (2025)
by: Jian, Chunjin, et al.
Published: (2025)
Do LLMs Dream of Discrete Algorithms?
by: Coelho Jr, Claudionor, et al.
Published: (2025)
by: Coelho Jr, Claudionor, et al.
Published: (2025)
Computable universal online learning
by: Kalociński, Dariusz, et al.
Published: (2025)
by: Kalociński, Dariusz, et al.
Published: (2025)
Scalable Interconnect Learning in Boolean Networks
by: Kresse, Fabian, et al.
Published: (2025)
by: Kresse, Fabian, et al.
Published: (2025)
Logic Gate Neural Networks are Good for Verification
by: Kresse, Fabian, et al.
Published: (2025)
by: Kresse, Fabian, et al.
Published: (2025)
Approximating Fixpoints of Approximated Functions
by: Baldan, Paolo, et al.
Published: (2025)
by: Baldan, Paolo, et al.
Published: (2025)
On Improving Deep Active Learning with Formal Verification
by: Spiegelman, Jonathan, et al.
Published: (2025)
by: Spiegelman, Jonathan, et al.
Published: (2025)
Explain Yourself, Briefly! Self-Explaining Neural Networks with Concise Sufficient Reasons
by: Bassan, Shahaf, et al.
Published: (2025)
by: Bassan, Shahaf, et al.
Published: (2025)
Learning Representations Through Contrastive Neural Model Checking
by: Krsmanovic, Vladimir, et al.
Published: (2025)
by: Krsmanovic, Vladimir, et al.
Published: (2025)
A Logical View of GNN-Style Computation and the Role of Activation Functions
by: Barceló, Pablo, et al.
Published: (2025)
by: Barceló, Pablo, et al.
Published: (2025)
Just-In-Time Piecewise-Linear Semantics for ReLU-type Networks
by: Duan, Hongyi, et al.
Published: (2025)
by: Duan, Hongyi, et al.
Published: (2025)
Nazrin: Atomic Tactics for Graph Neural Networks for Theorem Proving in Lean 4
by: Aniva, Leni, et al.
Published: (2026)
by: Aniva, Leni, et al.
Published: (2026)
Exponential Sample Complexity Separation between Flat and Hierarchical Agentic Theorem Provers
by: Sonoda, Sho, et al.
Published: (2026)
by: Sonoda, Sho, et al.
Published: (2026)
Diminishing Returns in Expanding Generative Models and Godel-Tarski-Lob Limits
by: Majumdar, Angshul
Published: (2026)
by: Majumdar, Angshul
Published: (2026)
Learning Better Representations From Less Data For Propositional Satisfiability
by: Ghanem, Mohamed, et al.
Published: (2024)
by: Ghanem, Mohamed, et al.
Published: (2024)
Deep Learning with Parametric Lenses
by: Cruttwell, Geoffrey S. H., et al.
Published: (2024)
by: Cruttwell, Geoffrey S. H., et al.
Published: (2024)
The Polynomial Counting Capabilities of Message Passing Neural Networks
by: Sälzer, Marco, et al.
Published: (2026)
by: Sälzer, Marco, et al.
Published: (2026)
Identification of Bivariate Causal Directionality Based on Anticipated Asymmetric Geometries
by: Glushkovsky, Alex
Published: (2026)
by: Glushkovsky, Alex
Published: (2026)
A PAC Learning Algorithm for LTL and Omega-regular Objectives in MDPs
by: Perez, Mateo, et al.
Published: (2023)
by: Perez, Mateo, et al.
Published: (2023)
Guiding LLM Temporal Logic Generation with Explicit Separation of Data and Control
by: Murphy, William, et al.
Published: (2024)
by: Murphy, William, et al.
Published: (2024)
Bisimulation Learning
by: Abate, Alessandro, et al.
Published: (2024)
by: Abate, Alessandro, et al.
Published: (2024)
TLINet: Differentiable Neural Network Temporal Logic Inference
by: Li, Danyang, et al.
Published: (2024)
by: Li, Danyang, et al.
Published: (2024)
Developing a Dataset-Adaptive, Normalized Metric for Machine Learning Model Assessment: Integrating Size, Complexity, and Class Imbalance
by: Ossenov, Serzhan
Published: (2024)
by: Ossenov, Serzhan
Published: (2024)
Similar Items
-
Linear Logic and the Hilbert Scheme
by: Troiani, William, et al.
Published: (2025) -
Linear Logic and Quantum Error Correcting Codes
by: Murfet, Daniel, et al.
Published: (2024) -
Logical GANs: Adversarial Learning through Ehrenfeucht Fraisse Games
by: Mannucci, Mirco A.
Published: (2025) -
From learnable objects to learnable random objects
by: Anderson, Aaron, et al.
Published: (2025) -
How (and when) can you fit examples to logic-based hypothesis classes over infinite structures?
by: Benedikt, Michael, et al.
Published: (2026)