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2020 – today
- 2024
[c87]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: 23850-23852- [c86]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: 194:1-194:14 - [c85]Mateo Espinosa Zarlenga, Swami Sankaranarayanan, Jerone T. A. Andrews, Zohreh Shams, Mateja Jamnik, Alice Xiang:
Efficient Bias Mitigation Without Privileged Information. ECCV (72) 2024: 148-166 - [c84]Evan Rex, Mateo Espinosa Zarlenga, Andrei Margeloiu, Mateja Jamnik:
From Must to May: Enabling Test-Time Feature Imputation and Interventions. HI-AI@KDD 2024: 74-86 - [c83]Urszula Julia Komorowska, Simon V. Mathis, Kieran Didi, Francisco Vargas, Pietro Lio, Mateja Jamnik:
Dynamics-Informed Protein Design with Structure Conditioning. ICLR 2024 - [c82]Xiangjian Jiang, Andrei Margeloiu, Nikola Simidjievski, Mateja Jamnik:
ProtoGate: Prototype-based Neural Networks with Global-to-local Feature Selection for Tabular Biomedical Data. ICML 2024 - [c81]Naveen Raman, Mateo Espinosa Zarlenga, Mateja Jamnik:
Understanding Inter-Concept Relationships in Concept-Based Models. ICML 2024 - [c80]Gabriele Ciravegna, Mateo Espinosa Zarlenga, Pietro Barbiero, Francesco Giannini, Zohreh Shams, Damien Garreau, Mateja Jamnik, Tania Cerquitelli:
Workshop on Human-Interpretable AI. KDD 2024: 6708-6709 - [c79]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: 345-351 - [e3]Gabriele Ciravegna, Mateo Espinosa Zarlenga, Pietro Barbiero, Zohreh Shams, Francesco Giannini, Damien Garreau, Mateja Jamnik, Tania Cerquitelli:
Proceedings of the KDD Workshop on Human-Interpretable AI 2024 co-located with 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024), Centre de Convencions Internacional de Barcelona, Spain, August 26, 2024. CEUR Workshop Proceedings 3841, CEUR-WS.org 2024 [contents] - [i49]Naveen Raman, Mateo Espinosa Zarlenga, Juyeon Heo, Mateja Jamnik:
Do Concept Bottleneck Models Obey Locality? CoRR abs/2401.01259 (2024) - [i48]Tiansi Dong, Mateja Jamnik, Pietro Liò:
Sphere Neural-Networks for Rational Reasoning. CoRR abs/2403.15297 (2024) - [i47]Naveen Raman, Mateo Espinosa Zarlenga, Mateja Jamnik:
Understanding Inter-Concept Relationships in Concept-Based Models. CoRR abs/2405.18217 (2024) - [i46]Konstantin Hemker, Nikola Simidjievski, Mateja Jamnik:
MM-Lego: Modular Biomedical Multimodal Models with Minimal Fine-Tuning. CoRR abs/2405.19950 (2024) - [i45]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 abs/2406.01805 (2024) - [i44]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 abs/2406.04165 (2024) - [i43]Andrei Margeloiu, Xiangjian Jiang, Nikola Simidjievski, Mateja Jamnik:
TabEBM: A Tabular Data Augmentation Method with Distinct Class-Specific Energy-Based Models. CoRR abs/2409.16118 (2024) - [i42]Andy Lo, Albert Q. Jiang, Wenda Li, Mateja Jamnik:
End-to-End Ontology Learning with Large Language Models. CoRR abs/2410.23584 (2024) - 2023
- [j8]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) - [c78]Andrei Margeloiu, Nikola Simidjievski, Pietro Liò, Mateja Jamnik:
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data. AAAI 2023: 9081-9089 - [c77]Mateo Espinosa Zarlenga, Pietro Barbiero, Zohreh Shams, Dmitry Kazhdan, Umang Bhatt, Adrian Weller, Mateja Jamnik:
Towards Robust Metrics for Concept Representation Evaluation. AAAI 2023: 11791-11799 - [c76]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: 869-889 - [c75]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: 438:1-438:14 - [c74]Mateja Jamnik:
How Can We Make Trustworthy AI? (Invited Talk). FSCD 2023: 2:1-2:1 - [c73]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 - [c72]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: 1801-1825 - [c71]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: 422-423 - [c70]Mateo Espinosa Zarlenga, Katie Collins, Krishnamurthy Dvijotham, Adrian Weller, Zohreh Shams, Mateja Jamnik:
Learning to Receive Help: Intervention-Aware Concept Embedding Models. NeurIPS 2023 - [c69]Konstantin Hemker, Zohreh Shams, Mateja Jamnik:
CGXplain: Rule-Based Deep Neural Network Explanations Using Dual Linear Programs. TML4H 2023: 60-72 - [c68]Yuri Sato, Gem Stapleton, Mateja Jamnik, Zohreh Shams, Andrew Blake:
Human Visual Consistency-Checking in the Real World Ontologies. VL/HCC 2023: 249-251 - [c67]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: 233-255 - [i41]Mateo Espinosa Zarlenga, Pietro Barbiero, Zohreh Shams, Dmitry Kazhdan, Umang Bhatt, Adrian Weller, Mateja Jamnik:
Towards Robust Metrics for Concept Representation Evaluation. CoRR abs/2301.10367 (2023) - [i40]Dmitry Kazhdan, Botty Dimanov, Lucie Charlotte Magister, Pietro Barbiero, Mateja Jamnik, Pietro Liò:
GCI: A (G)raph (C)oncept (I)nterpretation Framework. CoRR abs/2302.04899 (2023) - [i39]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 abs/2303.12872 (2023) - [i38]Konstantin Hemker, Zohreh Shams, Mateja Jamnik:
CGXplain: Rule-Based Deep Neural Network Explanations Using Dual Linear Programs. CoRR abs/2304.05207 (2023) - [i37]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 abs/2304.14068 (2023) - [i36]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 abs/2306.01694 (2023) - [i35]Xiangjian Jiang, Andrei Margeloiu, Nikola Simidjievski, Mateja Jamnik:
ProtoGate: Prototype-based Neural Networks with Local Feature Selection for Tabular Biomedical Data. CoRR abs/2306.12330 (2023) - [i34]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 abs/2306.15661 (2023) - [i33]Mateo Espinosa Zarlenga, Katherine M. Collins, Krishnamurthy Dvijotham, Adrian Weller, Zohreh Shams, Mateja Jamnik:
Learning to Receive Help: Intervention-Aware Concept Embedding Models. CoRR abs/2309.16928 (2023) - [i32]Albert Q. Jiang, Wenda Li, Mateja Jamnik:
Multilingual Mathematical Autoformalization. CoRR abs/2311.03755 (2023) - [i31]Konstantin Hemker, Nikola Simidjievski, Mateja Jamnik:
HEALNet - Hybrid Multi-Modal Fusion for Heterogeneous Biomedical Data. CoRR abs/2311.09115 (2023) - 2022
- [j7]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): 1320-1327 (2022) - [c66]Agnieszka Slowik, Léon Bottou, Sean B. Holden, Mateja Jamnik:
On the Relation between Distributionally Robust Optimization and Data Curation (Student Abstract). AAAI 2022: 13053-13054 - [c65]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 - [c64]Peter C.-H. Cheng, Aaron Stockdill, Grecia Garcia Garcia, Daniel Raggi, Mateja Jamnik:
Representational Interpretive Structure: Theory and Notation. Diagrams 2022: 54-69 - [c63]Sean McGrath, Andrew Blake, Gem Stapleton, Anestis Touloumis, Peter Chapman, Mateja Jamnik, Zohreh Shams:
Evaluating Colour in Concept Diagrams. Diagrams 2022: 168-184 - [c62]Daniel Raggi, Gem Stapleton, Mateja Jamnik, Aaron Stockdill, Grecia Garcia Garcia, Peter C.-H. Cheng:
Oruga: an avatar of Representational Systems Theory. HLC 2022: 1-5 - [c61]Aaron Stockdill, Grecia Garcia Garcia, Peter C.-H. Cheng, Daniel Raggi, Mateja Jamnik:
Cognitive Analysis for Representation Change. HLC 2022: 6-10 - [c60]Paul Scherer, Pietro Liò, Mateja Jamnik:
Distributed Representations of Graphs for Drug Pair Scoring. LoG 2022: 22 - [c59]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 - [c58]Yuhuai Wu, Albert Qiaochu Jiang, Wenda Li, Markus N. Rabe, Charles Staats, Mateja Jamnik, Christian Szegedy:
Autoformalization with Large Language Models. NeurIPS 2022 - [c57]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 - [c56]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: 1-6 - [p2]Mateja Jamnik, Peter C.-H. Cheng:
Endowing Machines with the Expert Human Ability to Select Representations: Why and How. Human-Like Machine Intelligence 2022: 355-378 - [i30]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 abs/2205.10893 (2022) - [i29]Yuhuai Wu, Albert Q. Jiang, Wenda Li, Markus N. Rabe, Charles Staats, Mateja Jamnik, Christian Szegedy:
Autoformalization with Large Language Models. CoRR abs/2205.12615 (2022) - [i28]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 abs/2206.03172 (2022) - [i27]Lucie Charlotte Magister, Pietro Barbiero, Dmitry Kazhdan, Federico Siciliano, Gabriele Ciravegna, Fabrizio Silvestri, Pietro Liò, Mateja Jamnik:
Encoding Concepts in Graph Neural Networks. CoRR abs/2207.13586 (2022) - [i26]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 abs/2209.09056 (2022) - [i25]Paul Scherer, Pietro Liò, Mateja Jamnik:
Distributed representations of graphs for drug pair scoring. CoRR abs/2209.09383 (2022) - [i24]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 abs/2210.12283 (2022) - [i23]Andrei Margeloiu, Nikola Simidjievski, Pietro Lio', Mateja Jamnik:
Graph-Conditioned MLP for High-Dimensional Tabular Biomedical Data. CoRR abs/2211.06302 (2022) - [i22]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 abs/2211.07650 (2022) - [i21]Yana Lishkova, Paul Scherer, Steffen Ridderbusch, Mateja Jamnik, Pietro Liò, Sina Ober-Blöbaum, Christian Offen:
Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery. CoRR abs/2211.10830 (2022) - [i20]Andrei Margeloiu, Nikola Simidjievski, Pietro Liò, Mateja Jamnik:
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data. CoRR abs/2211.15616 (2022) - 2021
- [c55]Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Chris Pal:
Structural Inductive Biases in Emergent Communication. CogSci 2021 - [c54]Aaron Stockdill, Daniel Raggi, Mateja Jamnik, Grecia Garcia Garcia, Peter C.-H. Cheng:
Considerations in Representation Selection for Problem Solving: A Review. Diagrams 2021: 35-51 - [c53]Peter C.-H. Cheng, Grecia Garcia Garcia, Daniel Raggi, Aaron Stockdill, Mateja Jamnik:
Cognitive Properties of Representations: A Framework. Diagrams 2021: 415-430 - [c52]Fiorenzo Colarusso, Peter C.-H. Cheng, Grecia Garcia Garcia, Daniel Raggi, Mateja Jamnik:
Observing Strategies of Drawing Data Representations. Diagrams 2021: 537-552 - [c51]Edward W. Ayers, Mateja Jamnik, William T. Gowers:
A Graphical User Interface Framework for Formal Verification. ITP 2021: 4:1-4:16 - [i19]Dmitry Kazhdan, Botty Dimanov, Helena Andrés-Terré, Mateja Jamnik, Pietro Liò, Adrian Weller:
Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches. CoRR abs/2104.06917 (2021) - [i18]Maleakhi A. Wijaya, Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik:
Failing Conceptually: Concept-Based Explanations of Dataset Shift. CoRR abs/2104.08952 (2021) - [i17]Andrei Margeloiu, Matthew Ashman, Umang Bhatt, Yanzhi Chen, Mateja Jamnik, Adrian Weller:
Do Concept Bottleneck Models Learn as Intended? CoRR abs/2105.04289 (2021) - [i16]Mateo Espinosa Zarlenga, Zohreh Shams, Mateja Jamnik:
Efficient Decompositional Rule Extraction for Deep Neural Networks. CoRR abs/2111.12628 (2021) - 2020
- [c50]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: 63-73 - [c49]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: 13919-13920 - [c48]Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik, Pietro Liò, Adrian Weller:
Now You See Me (CME): Concept-based Model Extraction. CIKM (Workshops) 2020 - [c47]Daniel Raggi, Aaron Stockdill, Mateja Jamnik, Grecia Garcia Garcia, Holly E. A. Sutherland, Peter C.-H. Cheng:
Dissecting Representations. Diagrams 2020: 144-152 - [c46]Botty Dimanov, Umang Bhatt, Mateja Jamnik, Adrian Weller:
You Shouldn't Trust Me: Learning Models Which Conceal Unfairness from Multiple Explanation Methods. ECAI 2020: 2473-2480 - [c45]Duo Wang, Mateja Jamnik, Pietro Liò:
Abstract Diagrammatic Reasoning with Multiplex Graph Networks. ICLR 2020 - [c44]Daniel Raggi, Gem Stapleton, Aaron Stockdill, Mateja Jamnik, Grecia Garcia Garcia, Peter C.-H. Cheng:
How to (Re)represent it? ICTAI 2020: 1224-1232 - [c43]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 - [c42]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: 1-5 - [i15]Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden:
Towards Graph Representation Learning in Emergent Communication. CoRR abs/2001.09063 (2020) - [i14]Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Christopher J. Pal:
Exploring Structural Inductive Biases in Emergent Communication. CoRR abs/2002.01335 (2020) - [i13]Yiren Zhao, Duo Wang, Xitong Gao, Robert D. Mullins, Pietro Liò, Mateja Jamnik:
Probabilistic Dual Network Architecture Search on Graphs. CoRR abs/2003.09676 (2020) - [i12]Duo Wang, Mateja Jamnik, Pietro Liò:
Generalisable Relational Reasoning With Comparators in Low-Dimensional Manifolds. CoRR abs/2006.08698 (2020) - [i11]Duo Wang, Mateja Jamnik, Pietro Liò:
Abstract Diagrammatic Reasoning with Multiplex Graph Networks. CoRR abs/2006.11197 (2020) - [i10]Yiren Zhao, Duo Wang, Daniel Bates, Robert D. Mullins, Mateja Jamnik, Pietro Liò:
Learned Low Precision Graph Neural Networks. CoRR abs/2009.09232 (2020) - [i9]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 abs/2010.00387 (2020) - [i8]Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik, Pietro Liò, Adrian Weller:
Now You See Me (CME): Concept-based Model Extraction. CoRR abs/2010.13233 (2020) - [i7]Nicholas Quek Wei Kiat, Duo Wang, Mateja Jamnik:
Pairwise Relations Discriminator for Unsupervised Raven's Progressive Matrices. CoRR abs/2011.01306 (2020) - [i6]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 abs/2011.10998 (2020) - [i5]Andrei Margeloiu, Nikola Simidjievski, Mateja Jamnik, Adrian Weller:
Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training. CoRR abs/2012.01166 (2020) - [i4]Dmitry Kazhdan, Botty Dimanov, Mateja Jamnik, Pietro Liò:
MEME: Generating RNN Model Explanations via Model Extraction. CoRR abs/2012.06954 (2020)
2010 – 2019
- 2019
- [j6]Yuri Sato, Gem Stapleton, Mateja Jamnik, Zohreh Shams:
Human inference beyond syllogisms: an approach using external graphical representations. Cogn. Process. 20(1): 103-115 (2019) - [c41]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: 3252 - [c40]Ian Oliver, John Howse, Gem Stapleton, Zohreh Shams, Mateja Jamnik:
Exploring and Conceptualising Attestation. ICCS 2019: 131-145 - [c39]Edward William Ayers, William T. Gowers, Mateja Jamnik:
A Human-Oriented Term Rewriting System. KI 2019: 76-86 - [c38]Daniel Raggi, Aaron Stockdill, Mateja Jamnik, Grecia Garcia Garcia, Holly E. A. Sutherland, Peter C.-H. Cheng:
Inspection and Selection of Representations. CICM 2019: 227-242 - [c37]Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson:
Bayesian Optimisation for Heuristic Configuration in Automated Theorem Proving. Vampire 2019: 45-51 - [i3]Duo Wang, Mateja Jamnik, Pietro Liò:
Unsupervised and interpretable scene discovery with Discrete-Attend-Infer-Repeat. CoRR abs/1903.06581 (2019) - [i2]Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson:
Bayesian Optimisation with Gaussian Processes for Premise Selection. CoRR abs/1909.09137 (2019) - [i1]Paul Scherer, Helena Andrés-Terré, Pietro Liò, Mateja Jamnik:
Decoupling feature propagation from the design of graph auto-encoders. CoRR abs/1910.08589 (2019) - 2018
- [c36]Yuri Sato, Gem Stapleton, Mateja Jamnik, Zohreh Shams:
Deductive reasoning about expressive statements using external graphical representations. CogSci 2018 - [c35]Zohreh Shams, Yuri Sato, Mateja Jamnik, Gem Stapleton:
Accessible Reasoning with Diagrams: From Cognition to Automation. Diagrams 2018: 247-263 - [c34]Gem Stapleton, Atsushi Shimojima, Mateja Jamnik:
The Observational Advantages of Euler Diagrams with Existential Import. Diagrams 2018: 313-329 - [c33]Duo Wang, Mateja Jamnik, Pietro Liò:
Investigating Diagrammatic Reasoning with Deep Neural Networks. Diagrams 2018: 390-398 - [c32]Zohreh Shams, Mateja Jamnik, Gem Stapleton, Yuri Sato:
iCon: A Diagrammatic Theorem Prover for Ontologies. KR 2018: 204-209 - 2017
- [j5]Gem Stapleton, Mateja Jamnik, Atsushi Shimojima:
What Makes an Effective Representation of Information: A Formal Account of Observational Advantages. J. Log. Lang. Inf. 26(2): 143-177 (2017) - [c31]Zohreh Shams, Mateja Jamnik, Gem Stapleton, Yuri Sato:
Reasoning with Concept Diagrams about Antipatterns. LPAR (Short Presentations) 2017: 27-42 - [c30]Zohreh Shams, Mateja Jamnik, Gem Stapleton, Yuri Sato:
Reasoning with Concept Diagrams About Antipatterns in Ontologies. CICM 2017: 255-271 - [c29]Yuri Sato, Gem Stapleton, Mateja Jamnik, Zohreh Shams, Andrew Blake:
How Network-based and set-based visualizations aid consistency checking in ontologies. VINCI 2017: 137-141 - 2016
- [c28]Gem Stapleton, Mateja Jamnik, Atsushi Shimojima:
Effective Representation of Information: Generalizing Free Rides. Diagrams 2016: 296-299 - [c27]Advait Sarkar, Martin Spott, Alan F. Blackwell, Mateja Jamnik:
Visual discovery and model-driven explanation of time series patterns. VL/HCC 2016: 78-86 - [c26]Sven Linker, Jim Burton, Mateja Jamnik:
Tactical Diagrammatic Reasoning. UITP 2016: 29-42 - [e2]Mateja Jamnik, Yuri Uesaka, Stephanie Elzer Schwartz:
Diagrammatic Representation and Inference - 9th International Conference, Diagrams 2016, Philadelphia, PA, USA, August 7-10, 2016, Proceedings. Lecture Notes in Computer Science 9781, Springer 2016, ISBN 978-3-319-42332-6 [contents] - 2015
- [j4]Matej Urbas, Mateja Jamnik, Gem Stapleton:
Speedith: A Reasoner for Spider Diagrams. J. Log. Lang. Inf. 24(4): 487-540 (2015) - [c25]Advait Sarkar, Alan F. Blackwell, Mateja Jamnik, Martin Spott:
Interaction with Uncertainty in Visualisations. EuroVis (Short Papers) 2015: 133-137 - [c24]Advait Sarkar, Mateja Jamnik, Alan F. Blackwell, Martin Spott:
Interactive visual machine learning in spreadsheets. VL/HCC 2015: 159-163 - 2014
- [c23]Matej Urbas, Mateja Jamnik:
A Framework for Heterogeneous Reasoning in Formal and Informal Domains. Diagrams 2014: 277-292 - [c22]Advait Sarkar, Alan F. Blackwell, Mateja Jamnik, Martin Spott:
Teach and try: A simple interaction technique for exploratory data modelling by end users. VL/HCC 2014: 53-56 - 2013
- [c21]Gem Stapleton, Mateja Jamnik, Matej Urbas:
Designing inference rules for spider diagrams. VL/HCC 2013: 19-26 - 2012
- [c20]Matej Urbas, Mateja Jamnik:
Diabelli: A Heterogeneous Proof System. IJCAR 2012: 559-566 - [c19]Matej Urbas, Mateja Jamnik, Gem Stapleton, Jean Flower:
Speedith: A Diagrammatic Reasoner for Spider Diagrams. Diagrams 2012: 163-177 - 2011
- [c18]Matej Urbas, Mateja Jamnik:
Heterogeneous Proofs: Spider Diagrams Meet Higher-Order Provers. ITP 2011: 376-382 - 2010
- [c17]Matej Urbas, Mateja Jamnik:
Heterogeneous Reasoning in Real Arithmetic. Diagrams 2010: 345-348 - [e1]Ashok K. Goel, Mateja Jamnik, N. Hari Narayanan:
Diagrammatic Representation and Inference, 6th International Conference, Diagrams 2010, Portland, OR, USA, August 9-11, 2010. Proceedings. Lecture Notes in Computer Science 6170, Springer 2010, ISBN 978-3-642-14599-5 [contents]
2000 – 2009
- 2008
- [j3]Christoph Benzmüller, Volker Sorge, Mateja Jamnik, Manfred Kerber:
Combined reasoning by automated cooperation. J. Appl. Log. 6(3): 318-342 (2008) - [c16]M. Ridsdale, Mateja Jamnik, Nick Benton, Josh Berdine:
Diagrammatic Reasoning in Separation Logic. Diagrams 2008: 408-411 - 2005
- [c15]Mateja Jamnik, Alan Bundy:
Psychological Validity of Schematic Proofs. Mechanizing Mathematical Reasoning 2005: 321-341 - [c14]Louise A. Dennis, Mateja Jamnik, Martin Pollet:
On the Comparison of Proof Planning Systems: lambdaCLAM, Omega and IsaPlanner. Calculemus 2005: 93-110 - 2004
- [c13]Daniel Winterstein, Alan Bundy, Mateja Jamnik:
On Differences between the Real and Physical Plane. Diagrams 2004: 29-31 - [c12]Daniel Winterstein, Alan Bundy, Corin A. Gurr, Mateja Jamnik:
An Experimental Comparison of Diagrammatic and Algebraic Logics. Diagrams 2004: 432-434 - [c11]Christoph Benzmüller, Volker Sorge, Mateja Jamnik, Manfred Kerber:
Can a Higher-Order and a First-Order Theorem Prover Cooperate?. LPAR 2004: 415-431 - 2003
- [j2]Mateja Jamnik, Manfred Kerber, Martin Pollet, Christoph Benzmüller:
Automatic Learning of Proof Methods in Proof Planning. Log. J. IGPL 11(6): 647-673 (2003) - [c10]Mateja Jamnik, Predrag Janicic:
Learning Strategies for Mechanised Building of Decision Procedures. FTP 2003: 174-189 - 2002
- [c9]Mateja Jamnik, Manfred Kerber, Martin Pollet:
Learn Omega-matic: System Description. CADE 2002: 150-155 - [c8]Daniel Winterstein, Alan Bundy, Corin A. Gurr, Mateja Jamnik:
Using Animation in Diagrammatic Theorem Proving. Diagrams 2002: 46-60 - [c7]Mateja Jamnik, Manfred Kerber, Martin Pollet:
Automatic Learning in Proof Planning. ECAI 2002: 282-286 - [p1]Mateja Jamnik, Alan Bundy, Ian Green:
On Automating Diagrammatic Proofs of Arithmetic Arguments. Diagrammatic Representation and Reasoning 2002: 315-338 - 2001
- [c6]Christoph Benzmüller, Mateja Jamnik, Manfred Kerber, Volker Sorge:
Experiments with an Agent-Oriented Reasoning System. KI/ÖGAI 2001: 409-424 - 2000
- [c5]Christoph Benzmüller, Mateja Jamnik, Manfred Kerber, Volker Sorge:
Resource Guided Concurrent Deduction. ARW 2000 - [c4]Daniel Winterstein, Alan Bundy, Mateja Jamnik:
A Proposal for Automating Diagrammatic Reasoning in Continuous Domains. Diagrams 2000: 286-299
1990 – 1999
- 1999
- [j1]Mateja Jamnik, Alan Bundy, Ian Green:
On Automating Diagrammatic Proofs of Arithmetic Arguments. J. Log. Lang. Inf. 8(3): 297-321 (1999) - [c3]Christoph Benzmüller, Mateja Jamnik, Manfred Kerber, Volker Sorge:
Agent based mathematical reasoning. Calculemus 1999: 340-351 - 1997
- [c2]Mateja Jamnik, Alan Bundy, Ian Green:
Automation of Diagrammatic Reasoning. IJCAI (1) 1997: 528-533 - [c1]Mateja Jamnik:
Automation of Diagrammatic Proofs in Mathematics. IJCAI 1997: 1541
Coauthor Index
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