Mateja Jamnik

ORCID

Publication Activity (10 Years)

Years Active: 1997-2024
Publications (10 Years): 109

Top Venues

Publications

Gabriele Ciravegna, Mateo Espinosa Zarlenga, Pietro Barbiero, Francesco Giannini, Zohreh Shams, Damien Garreau, Mateja Jamnik, Tania Cerquitelli
Workshop on Human-Interpretable AI. KDD (2024)
Alicja Ziarko, Albert Q. Jiang, Bartosz Piotrowski, Wenda Li, Mateja Jamnik, Piotr Milos
Repurposing Language Models into Embedding Models: Finding the Compute-Optimal Recipe. CoRR (2024)
Tiansi Dong, Mateja Jamnik, Pietro Liò
Sphere Neural-Networks for Rational Reasoning. CoRR (2024)
Andrei Margeloiu, Adrián Bazaga, Nikola Simidjievski, Pietro Liò, Mateja Jamnik
TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting. CoRR (2024)
Peter C.-H. Cheng, Grecia Garcia Garcia, Daniel Raggi, Mateja Jamnik
A Human Information Processing Theory of the Interpretation of Visualizations: Demonstrating Its Utility. CHI (2024)
Urszula Julia Komorowska, Simon V. Mathis, Kieran Didi, Francisco Vargas, Pietro Lio, Mateja Jamnik
Dynamics-Informed Protein Design with Structure Conditioning. ICLR (2024)
Naveen Raman, Mateo Espinosa Zarlenga, Juyeon Heo, Mateja Jamnik
Do Concept Bottleneck Models Obey Locality? CoRR (2024)
Naveen Raman, Mateo Espinosa Zarlenga, Mateja Jamnik
Understanding Inter-Concept Relationships in Concept-Based Models. CoRR (2024)
Daniel Raggi, Gem Stapleton, Aaron Stockdill, Grecia Garcia Garcia, Peter C.-H. Cheng, Mateja Jamnik
Oruga: Implementation and Use of Representational Systems Theory. CICM (2024)
Lianlong Wu, Seewon Choi, Daniel Raggi, Aaron Stockdill, Grecia Garcia Garcia, Fiorenzo Colarusso, Peter C.-H. Cheng, Mateja Jamnik
Generation of Visual Representations for Multi-Modal Mathematical Knowledge. AAAI (2024)
Konstantin Hemker, Nikola Simidjievski, Mateja Jamnik
MM-Lego: Modular Biomedical Multimodal Models with Minimal Fine-Tuning. CoRR (2024)
Dmitry Kazhdan, Botty Dimanov, Lucie Charlotte Magister, Pietro Barbiero, Mateja Jamnik, Pietro Liò
GCI: A (G)raph (C)oncept (I)nterpretation Framework. CoRR (2023)
Konstantin Hemker, Zohreh Shams, Mateja Jamnik
CGXplain: Rule-Based Deep Neural Network Explanations Using Dual Linear Programs. CoRR (2023)
Mateo Espinosa Zarlenga, Zohreh Shams, Michael E. Nelson, Been Kim, Mateja Jamnik
TabCBM: Concept-based Interpretable Neural Networks for Tabular Data. Trans. Mach. Learn. Res. 2023 (2023)
Albert Q. Jiang, Wenda Li, Mateja Jamnik
Multilingual Mathematical Autoformalization. CoRR (2023)
Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Lio', Frédéric Precioso, Mateja Jamnik, Giuseppe Marra
Interpretable Neural-Symbolic Concept Reasoning. CoRR (2023)
Lucie Charlotte Magister, Pietro Barbiero, Dmitry Kazhdan, Federico Siciliano, Gabriele Ciravegna, Fabrizio Silvestri, Mateja Jamnik, Pietro Liò
Concept Distillation in Graph Neural Networks. xAI (3) (2023)
Katherine M. Collins, Albert Q. Jiang, Simon Frieder, Lionel Wong, Miri Zilka, Umang Bhatt, Thomas Lukasiewicz, Yuhuai Wu, Joshua B. Tenenbaum, William Hart, Timothy Gowers, Wenda Li, Adrian Weller, Mateja Jamnik
Evaluating Language Models for Mathematics through Interactions. CoRR (2023)
Konstantin Hemker, Nikola Simidjievski, Mateja Jamnik
HEALNet - Hybrid Multi-Modal Fusion for Heterogeneous Biomedical Data. CoRR (2023)
Yuri Sato, Gem Stapleton, Mateja Jamnik, Zohreh Shams, Andrew Blake
Human Visual Consistency-Checking in the Real World Ontologies. VL/HCC (2023)
Andrei Margeloiu, Nikola Simidjievski, Pietro Liò, Mateja Jamnik
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data. AAAI (2023)
Xiangjian Jiang, Andrei Margeloiu, Nikola Simidjievski, Mateja Jamnik
ProtoGate: Prototype-based Neural Networks with Local Feature Selection for Tabular Biomedical Data. CoRR (2023)
Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Lio, Frédéric Precioso, Mateja Jamnik, Giuseppe Marra
Interpretable Neural-Symbolic Concept Reasoning. ICML (2023)
Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Liò, Frédéric Precioso, Mateja Jamnik, Giuseppe Marra
Interpretable Neural-Symbolic Concept Reasoning. NeSy (2023)
Mateo Espinosa Zarlenga, Pietro Barbiero, Zohreh Shams, Dmitry Kazhdan, Umang Bhatt, Adrian Weller, Mateja Jamnik
Towards Robust Metrics for Concept Representation Evaluation. CoRR (2023)
Mateo Espinosa Zarlenga, Katherine M. Collins, Krishnamurthy Dvijotham, Adrian Weller, Zohreh Shams, Mateja Jamnik
Learning to Receive Help: Intervention-Aware Concept Embedding Models. CoRR (2023)
Mateo Espinosa Zarlenga, Pietro Barbiero, Zohreh Shams, Dmitry Kazhdan, Umang Bhatt, Adrian Weller, Mateja Jamnik
Towards Robust Metrics for Concept Representation Evaluation. AAAI (2023)
Katherine Maeve Collins, Matthew Barker, Mateo Espinosa Zarlenga, Naveen Raman, Umang Bhatt, Mateja Jamnik, Ilia Sucholutsky, Adrian Weller, Krishnamurthy Dvijotham
Human Uncertainty in Concept-Based AI Systems. AIES (2023)
Mateja Jamnik
How Can We Make Trustworthy AI? (Invited Talk). FSCD (2023)
Mateo Espinosa Zarlenga, Katie Collins, Krishnamurthy Dvijotham, Adrian Weller, Zohreh Shams, Mateja Jamnik
Learning to Receive Help: Intervention-Aware Concept Embedding Models. NeurIPS (2023)
Albert Qiaochu Jiang, Sean Welleck, Jin Peng Zhou, Timothée Lacroix, Jiacheng Liu, Wenda Li, Mateja Jamnik, Guillaume Lample, Yuhuai Wu
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs. ICLR (2023)
Konstantin Hemker, Zohreh Shams, Mateja Jamnik
CGXplain: Rule-Based Deep Neural Network Explanations Using Dual Linear Programs. TML4H (2023)
Katherine M. Collins, Matthew Barker, Mateo Espinosa Zarlenga, Naveen Raman, Umang Bhatt, Mateja Jamnik, Ilia Sucholutsky, Adrian Weller, Krishnamurthy Dvijotham
Human Uncertainty in Concept-Based AI Systems. CoRR (2023)
Navindu Leelarathna, Andrei Margeloiu, Mateja Jamnik, Nikola Simidjievski
Enhancing Representation Learning on High-Dimensional, Small-Size Tabular Data: A Divide and Conquer Method with Ensembled VAEs. CoRR (2023)
Fiorenzo Colarusso, Peter C.-H. Cheng, Grecia Garcia Garcia, Aaron Stockdill, Daniel Raggi, Mateja Jamnik
A novel interaction for competence assessment using micro-behaviors: : Extending CACHET to graphs and charts. CHI (2023)
Yuhuai Wu, Albert Q. Jiang, Wenda Li, Markus N. Rabe, Charles Staats, Mateja Jamnik, Christian Szegedy
Autoformalization with Large Language Models. CoRR (2022)
Aaron Stockdill, Grecia Garcia Garcia, Peter C.-H. Cheng, Daniel Raggi, Mateja Jamnik
Cognitive Analysis for Representation Change. HLC (2022)
Daniel Raggi, Gem Stapleton, Mateja Jamnik, Aaron Stockdill, Grecia Garcia Garcia, Peter C.-H. Cheng
Oruga: an avatar of Representational Systems Theory. HLC (2022)
Albert Qiaochu Jiang, Wenda Li, Szymon Tworkowski, Konrad Czechowski, Tomasz Odrzygózdz, Piotr Milos, Yuhuai Wu, Mateja Jamnik
Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers. NeurIPS (2022)
Aaron Stockdill, Gem Stapleton, Daniel Raggi, Mateja Jamnik, Grecia Garcia Garcia, Peter C.-H. Cheng
Examining Experts' Recommendations of Representational Systems for Problem Solving. VL/HCC (2022)
Agnieszka Slowik, Léon Bottou, Sean B. Holden, Mateja Jamnik
On the Relation between Distributionally Robust Optimization and Data Curation (Student Abstract). AAAI (2022)
Yana Lishkova, Paul Scherer, Steffen Ridderbusch, Mateja Jamnik, Pietro Liò, Sina Ober-Blöbaum, Christian Offen
Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery. CoRR (2022)
Andrei Margeloiu, Nikola Simidjievski, Pietro Lio', Mateja Jamnik
Graph-Conditioned MLP for High-Dimensional Tabular Biomedical Data. CoRR (2022)
Shea Cardozo, Gabriel Islas Montero, Dmitry Kazhdan, Botty Dimanov, Maleakhi A. Wijaya, Mateja Jamnik, Pietro Liò
Explainer Divergence Scores (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations. CIKM Workshops (2022)
Yuhuai Wu, Albert Qiaochu Jiang, Wenda Li, Markus N. Rabe, Charles Staats, Mateja Jamnik, Christian Szegedy
Autoformalization with Large Language Models. NeurIPS (2022)
Paul Scherer, Pietro Liò, Mateja Jamnik
Distributed representations of graphs for drug pair scoring. CoRR (2022)
Albert Q. Jiang, Wenda Li, Szymon Tworkowski, Konrad Czechowski, Tomasz Odrzygózdz, Piotr Milos, Yuhuai Wu, Mateja Jamnik
Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers. CoRR (2022)
Paul Scherer, Pietro Liò, Mateja Jamnik
Distributed Representations of Graphs for Drug Pair Scoring. LoG (2022)
Paul Scherer, Maja Trebacz, Nikola Simidjievski, Ramón Viñas, Zohreh Shams, Helena Andrés-Terré, Mateja Jamnik, Pietro Liò
Unsupervised construction of computational graphs for gene expression data with explicit structural inductive biases. Bioinform. 38 (5) (2022)
Daniel Raggi, Gem Stapleton, Mateja Jamnik, Aaron Stockdill, Grecia Garcia Garcia, Peter C.-H. Cheng
Representational Systems Theory: A Unified Approach to Encoding, Analysing and Transforming Representations. CoRR (2022)
Sean McGrath, Andrew Blake, Gem Stapleton, Anestis Touloumis, Peter Chapman, Mateja Jamnik, Zohreh Shams
Evaluating Colour in Concept Diagrams. Diagrams (2022)
Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frédéric Precioso, Stefano Melacci, Adrian Weller, Pietro Liò, Mateja Jamnik
Concept Embedding Models. CoRR (2022)
Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, Wenda Li, Jiacheng Liu, Mateja Jamnik, Timothée Lacroix, Yuhuai Wu, Guillaume Lample
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs. CoRR (2022)
Lucie Charlotte Magister, Pietro Barbiero, Dmitry Kazhdan, Federico Siciliano, Gabriele Ciravegna, Fabrizio Silvestri, Pietro Liò, Mateja Jamnik
Encoding Concepts in Graph Neural Networks. CoRR (2022)
Andrei Margeloiu, Nikola Simidjievski, Pietro Liò, Mateja Jamnik
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data. CoRR (2022)
Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frédéric Precioso, Stefano Melacci, Adrian Weller, Pietro Lió, Mateja Jamnik
Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off. NeurIPS (2022)
Shea Cardozo, Gabriel Islas Montero, Dmitry Kazhdan, Botty Dimanov, Maleakhi A. Wijaya, Mateja Jamnik, Pietro Liò
Explainer Divergence Scores (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations. CoRR (2022)
Peter C.-H. Cheng, Aaron Stockdill, Grecia Garcia Garcia, Daniel Raggi, Mateja Jamnik
Representational Interpretive Structure: Theory and Notation. Diagrams (2022)
Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Chris Pal
Structural Inductive Biases in Emergent Communication. CogSci (2021)
Maleakhi A. Wijaya, Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik
Failing Conceptually: Concept-Based Explanations of Dataset Shift. CoRR (2021)
Dmitry Kazhdan, Botty Dimanov, Helena Andrés-Terré, Mateja Jamnik, Pietro Liò, Adrian Weller
Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches. CoRR (2021)
Mateo Espinosa Zarlenga, Zohreh Shams, Mateja Jamnik
Efficient Decompositional Rule Extraction for Deep Neural Networks. CoRR (2021)
Aaron Stockdill, Daniel Raggi, Mateja Jamnik, Grecia Garcia Garcia, Peter C.-H. Cheng
Considerations in Representation Selection for Problem Solving: A Review. Diagrams (2021)
Fiorenzo Colarusso, Peter C.-H. Cheng, Grecia Garcia Garcia, Daniel Raggi, Mateja Jamnik
Observing Strategies of Drawing Data Representations. Diagrams (2021)
Peter C.-H. Cheng, Grecia Garcia Garcia, Daniel Raggi, Aaron Stockdill, Mateja Jamnik
Cognitive Properties of Representations: A Framework. Diagrams (2021)
Edward W. Ayers, Mateja Jamnik, William T. Gowers
A Graphical User Interface Framework for Formal Verification. ITP (2021)
Andrei Margeloiu, Matthew Ashman, Umang Bhatt, Yanzhi Chen, Mateja Jamnik, Adrian Weller
Do Concept Bottleneck Models Learn as Intended? CoRR (2021)
Daniel Raggi, Aaron Stockdill, Mateja Jamnik, Grecia Garcia Garcia, Holly E. A. Sutherland, Peter C.-H. Cheng
Dissecting Representations. Diagrams (2020)
Daniel Raggi, Gem Stapleton, Aaron Stockdill, Mateja Jamnik, Grecia Garcia Garcia, Peter C.-H. Cheng
How to (Re)represent it? ICTAI (2020)
Botty Dimanov, Umang Bhatt, Mateja Jamnik, Adrian Weller
You Shouldn't Trust Me: Learning Models Which Conceal Unfairness from Multiple Explanation Methods. ECAI (2020)
Aaron Stockdill, Daniel Raggi, Mateja Jamnik, Grecia Garcia Garcia, Holly E. A. Sutherland, Peter C.-H. Cheng, Advait Sarkar
Cross-domain Correspondences for Explainable Recommendations. ExSS-ATEC@IUI (2020)
Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik, Pietro Liò, Adrian Weller
Now You See Me (CME): Concept-based Model Extraction. CIKM (Workshops) (2020)
Aaron Stockdill, Daniel Raggi, Mateja Jamnik, Grecia Garcia Garcia, Holly E. A. Sutherland, Peter C.-H. Cheng, Advait Sarkar
Correspondence-based analogies for choosing problem representations. VL/HCC (2020)
Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson
Bayesian Optimisation for Premise Selection in Automated Theorem Proving (Student Abstract). AAAI (2020)
Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik, Pietro Liò
MEME: Generating RNN Model Explanations via Model Extraction. CoRR (2020)
Botty Dimanov, Umang Bhatt, Mateja Jamnik, Adrian Weller
You Shouldn't Trust Me: Learning Models Which Conceal Unfairness From Multiple Explanation Methods. SafeAI@AAAI (2020)
Duo Wang, Mateja Jamnik, Pietro Liò
Generalisable Relational Reasoning With Comparators in Low-Dimensional Manifolds. CoRR (2020)
Andrei Margeloiu, Nikola Simidjievski, Mateja Jamnik, Adrian Weller
Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training. CoRR (2020)
Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Christopher J. Pal
Exploring Structural Inductive Biases in Emergent Communication. CoRR (2020)
Yiren Zhao, Duo Wang, Daniel Bates, Robert D. Mullins, Mateja Jamnik, Pietro Liò
Learned Low Precision Graph Neural Networks. CoRR (2020)
Duo Wang, Mateja Jamnik, Pietro Liò
Abstract Diagrammatic Reasoning with Multiplex Graph Networks. ICLR (2020)
Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden
Towards Graph Representation Learning in Emergent Communication. CoRR (2020)
Maja Trebacz, Zohreh Shams, Mateja Jamnik, Paul Scherer, Nikola Simidjievski, Helena Andrés-Terré, Pietro Liò
Using ontology embeddings for structural inductive bias in gene expression data analysis. CoRR (2020)
Nicholas Quek Wei Kiat, Duo Wang, Mateja Jamnik
Pairwise Relations Discriminator for Unsupervised Raven's Progressive Matrices. CoRR (2020)
Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik, Pietro Liò, Adrian Weller
Now You See Me (CME): Concept-based Model Extraction. CoRR (2020)
Paul Scherer, Maja Trebacz, Nikola Simidjievski, Zohreh Shams, Helena Andrés-Terré, Pietro Liò, Mateja Jamnik
Incorporating network based protein complex discovery into automated model construction. CoRR (2020)
Duo Wang, Mateja Jamnik, Pietro Liò
Abstract Diagrammatic Reasoning with Multiplex Graph Networks. CoRR (2020)
Yiren Zhao, Duo Wang, Xitong Gao, Robert D. Mullins, Pietro Liò, Mateja Jamnik
Probabilistic Dual Network Architecture Search on Graphs. CoRR (2020)
Daniel Raggi, Aaron Stockdill, Mateja Jamnik, Grecia Garcia Garcia, Holly E. A. Sutherland, Peter C.-H. Cheng
Inspection and Selection of Representations. CICM (2019)
Ian Oliver, John Howse, Gem Stapleton, Zohreh Shams, Mateja Jamnik
Exploring and Conceptualising Attestation. ICCS (2019)
Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson
Bayesian Optimisation with Gaussian Processes for Premise Selection. CoRR (2019)
Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson
Bayesian Optimisation for Heuristic Configuration in Automated Theorem Proving. Vampire (2019)
Duo Wang, Mateja Jamnik, Pietro Liò
Unsupervised and interpretable scene discovery with Discrete-Attend-Infer-Repeat. CoRR (2019)
Yuri Sato, Gem Stapleton, Mateja Jamnik, Zohreh Shams
Human inference beyond syllogisms: an approach using external graphical representations. Cogn. Process. 20 (1) (2019)
Peter C.-H. Cheng, Grecia Garcia Garcia, Holly E. A. Sutherland, Daniel Raggi, Aaron Stockdill, Mateja Jamnik
Elucidating the Cognitive Anatomy of Representation Systems. CogSci (2019)
Paul Scherer, Helena Andrés-Terré, Pietro Liò, Mateja Jamnik
Decoupling feature propagation from the design of graph auto-encoders. CoRR (2019)
Edward William Ayers, William T. Gowers, Mateja Jamnik
A Human-Oriented Term Rewriting System. KI (2019)
Zohreh Shams, Mateja Jamnik, Gem Stapleton, Yuri Sato
iCon: A Diagrammatic Theorem Prover for Ontologies. KR (2018)
Zohreh Shams, Yuri Sato, Mateja Jamnik, Gem Stapleton
Accessible Reasoning with Diagrams: From Cognition to Automation. Diagrams (2018)
Yuri Sato, Gem Stapleton, Mateja Jamnik, Zohreh Shams
Deductive reasoning about expressive statements using external graphical representations. CogSci (2018)

Mateja Jamnik.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Mateja Jamnik