What makes an Ensemble (Un) Interpretable?
Fuente:
arXiv
Saved in:
| Main Authors: | Bassan, Shahaf, Amir, Guy, Zehavi, Meirav, Katz, Guy |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Hard to Explain: On the Computational Hardness of In-Distribution Model Interpretation
by: Amir, Guy, et al.
Published: (2024)
by: Amir, Guy, et al.
Published: (2024)
Local vs. Global Interpretability: A Computational Complexity Perspective
by: Bassan, Shahaf, et al.
Published: (2024)
by: Bassan, Shahaf, et al.
Published: (2024)
On the Computational Tractability of the (Many) Shapley Values
by: Marzouk, Reda, et al.
Published: (2025)
by: Marzouk, Reda, et al.
Published: (2025)
Formal Mechanistic Interpretability: Automated Circuit Discovery with Provable Guarantees
by: Hadad, Itamar, et al.
Published: (2026)
by: Hadad, Itamar, et al.
Published: (2026)
Provably Explaining Neural Additive Models
by: Bassan, Shahaf, et al.
Published: (2026)
by: Bassan, Shahaf, et al.
Published: (2026)
Additive Models Explained: A Computational Complexity Approach
by: Bassan, Shahaf, et al.
Published: (2025)
by: Bassan, Shahaf, et al.
Published: (2025)
Verified SHAP: Provable Bounds for Exact Shapley Values of Neural Networks
by: Boetius, David, et al.
Published: (2026)
by: Boetius, David, et al.
Published: (2026)
Unifying Formal Explanations: A Complexity-Theoretic Perspective
by: Bassan, Shahaf, et al.
Published: (2026)
by: Bassan, Shahaf, et al.
Published: (2026)
Explaining, Fast and Slow: Abstraction and Refinement of Provable Explanations
by: Bassan, Shahaf, et al.
Published: (2025)
by: Bassan, Shahaf, et al.
Published: (2025)
SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelism
by: Marzouk, Reda, et al.
Published: (2025)
by: Marzouk, Reda, 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)
Verifying the Generalization of Deep Learning to Out-of-Distribution Domains
by: Amir, Guy, et al.
Published: (2024)
by: Amir, Guy, et al.
Published: (2024)
Verifying Quantized Graph Neural Networks is PSPACE-complete
by: Sälzer, Marco, et al.
Published: (2025)
by: Sälzer, Marco, et al.
Published: (2025)
The Descriptive Complexity of Graph Neural Networks
by: Grohe, Martin
Published: (2023)
by: Grohe, Martin
Published: (2023)
Is uniform expressivity too restrictive? Towards efficient expressivity of graph neural networks
by: Khalife, Sammy, et al.
Published: (2024)
by: Khalife, Sammy, et al.
Published: (2024)
The Complexity of Verifying Feedforward Neural Networks in Quantised Settings
by: Alsmann, Eric, et al.
Published: (2026)
by: Alsmann, Eric, et al.
Published: (2026)
Limits of Deep Learning: Sequence Modeling through the Lens of Complexity Theory
by: Zubić, Nikola, et al.
Published: (2024)
by: Zubić, Nikola, et al.
Published: (2024)
Shield Synthesis for LTL Modulo Theories
by: Rodriguez, Andoni, et al.
Published: (2024)
by: Rodriguez, Andoni, et al.
Published: (2024)
Marabou 2.0: A Versatile Formal Analyzer of Neural Networks
by: Wu, Haoze, et al.
Published: (2024)
by: Wu, Haoze, et al.
Published: (2024)
The Expressive Power of Transformers with Chain of Thought
by: Merrill, William, et al.
Published: (2023)
by: Merrill, William, et al.
Published: (2023)
Proof Minimization in Neural Network Verification
by: Isac, Omri, et al.
Published: (2025)
by: Isac, Omri, 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)
The Computational Complexity of Satisfiability in State Space Models
by: Alsmann, Eric, et al.
Published: (2025)
by: Alsmann, Eric, et al.
Published: (2025)
Verifying Quantized GNNs With Readout Is Decidable But Highly Intractable
by: Chernobrovkin, Artem, et al.
Published: (2025)
by: Chernobrovkin, Artem, et al.
Published: (2025)
The Reachability Problem for Neural-Network Control Systems
by: Schilling, Christian, et al.
Published: (2024)
by: Schilling, Christian, et al.
Published: (2024)
Transformer Encoder Satisfiability: Complexity and Impact on Formal Reasoning
by: Sälzer, Marco, et al.
Published: (2024)
by: Sälzer, Marco, et al.
Published: (2024)
Primitive Recursion without Composition: Dynamical Characterizations, from Neural Networks to Polynomial ODEs
by: Bournez, Olivier
Published: (2026)
by: Bournez, Olivier
Published: (2026)
A Characterization of Basic Feasible Functionals Through Higher-Order Rewriting and Tuple Interpretations
by: Baillot, Patrick, et al.
Published: (2024)
by: Baillot, Patrick, et al.
Published: (2024)
Transductive Learning Is Compact
by: Asilis, Julian, et al.
Published: (2024)
by: Asilis, Julian, et al.
Published: (2024)
On Kernelization with Access to NP-Oracles
by: Molter, Hendrik, et al.
Published: (2025)
by: Molter, Hendrik, et al.
Published: (2025)
The Proof Analysis Problem
by: Arteche, Noel, et al.
Published: (2025)
by: Arteche, Noel, et al.
Published: (2025)
Effective Versions of Strong Measure Zero
by: Rayman, Matthew
Published: (2025)
by: Rayman, Matthew
Published: (2025)
Meta-Mathematics of Computational Complexity Theory
by: Oliveira, Igor C.
Published: (2025)
by: Oliveira, Igor C.
Published: (2025)
On the consistency of stronger lower bounds for NEXP
by: Thapen, Neil
Published: (2025)
by: Thapen, Neil
Published: (2025)
Functional variant of Polynomial Analogue of Gandy's Fixed Point Theorem
by: Nechesov, Andrey
Published: (2024)
by: Nechesov, Andrey
Published: (2024)
Proof Complexity of Linear Logics
by: Tabatabai, Amirhossein Akbar, et al.
Published: (2026)
by: Tabatabai, Amirhossein Akbar, et al.
Published: (2026)
An order out of nowhere: a new algorithm for infinite-domain CSPs
by: Mottet, Antoine, et al.
Published: (2023)
by: Mottet, Antoine, et al.
Published: (2023)
Proof complexity of positive branching programs
by: Das, Anupam, et al.
Published: (2021)
by: Das, Anupam, et al.
Published: (2021)
Parallelism and Adaptivity in Student-Teacher Witnessing
by: Ježil, Ondřej, et al.
Published: (2026)
by: Ježil, Ondřej, et al.
Published: (2026)
Similar Items
-
Hard to Explain: On the Computational Hardness of In-Distribution Model Interpretation
by: Amir, Guy, et al.
Published: (2024) -
Local vs. Global Interpretability: A Computational Complexity Perspective
by: Bassan, Shahaf, et al.
Published: (2024) -
On the Computational Tractability of the (Many) Shapley Values
by: Marzouk, Reda, et al.
Published: (2025) -
Formal Mechanistic Interpretability: Automated Circuit Discovery with Provable Guarantees
by: Hadad, Itamar, et al.
Published: (2026) -
Provably Explaining Neural Additive Models
by: Bassan, Shahaf, et al.
Published: (2026)