Publications | Max Planck Institute for Intelligent Systems

2023

Fairness in Machine Learning: Limitations and Opportunities

Barocas, S., Hardt, M., Narayanan, A.

MIT Press, December 2023 (book)

Abstract

An introduction to the intellectual foundations and practical utility of the recent work on fairness and machine learning. Fairness and Machine Learning introduces advanced undergraduate and graduate students to the intellectual foundations of this recently emergent field, drawing on a diverse range of disciplinary perspectives to identify the opportunities and hazards of automated decision-making. It surveys the risks in many applications of machine learning and provides a review of an emerging set of proposed solutions, showing how even well-intentioned applications may give rise to objectionable results. It covers the statistical and causal measures used to evaluate the fairness of machine learning models as well as the procedural and substantive aspects of decision-making that are core to debates about fairness, including a review of legal and philosophical perspectives on discrimination. This incisive textbook prepares students of machine learning to do quantitative work on fairness while reflecting critically on its foundations and its practical utility.• Introduces the technical and normative foundations of fairness in automated decision-making• Covers the formal and computational methods for characterizing and addressing problems• Provides a critical assessment of their intellectual foundations and practical utility• Features rich pedagogy and extensive instructor resources

2023

sf Barocas, S., Hardt, M., Narayanan, A. Fairness in Machine Learning: Limitations and Opportunities MIT Press, December 2023 (book)

Denoising Representation Learning for Causal Discovery

Sakenyte, U.

Université de Genèva, Switzerland, December 2023, external supervision (mastersthesis)

ei Sakenyte, U. Denoising Representation Learning for Causal Discovery Université de Genèva, Switzerland, December 2023, external supervision (mastersthesis)

Efficient Sampling from Differentiable Matrix Elements

Kofler, A.

Technical University of Munich, Germany, September 2023 (mastersthesis)

ei Kofler, A. Efficient Sampling from Differentiable Matrix Elements Technical University of Munich, Germany, September 2023 (mastersthesis)

Intrinsic complexity and mechanisms of expressivity of cortical neurons

Spieler, A. M.

University of Tübingen, Germany, March 2023 (mastersthesis)

ei Spieler, A. M. Intrinsic complexity and mechanisms of expressivity of cortical neurons University of Tübingen, Germany, March 2023 (mastersthesis)

CausalEffect Estimation by Combining Observational and Interventional Data

Kladny, K.

ETH Zurich, Switzerland, February 2023 (mastersthesis)

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lds ei Kladny, K. CausalEffect Estimation by Combining Observational and Interventional Data ETH Zurich, Switzerland, February 2023 (mastersthesis)

Towards Generative Machine Teaching

Qui, Z.

Technical University of Munich, Germany, February 2023 (mastersthesis)

ei Qui, Z. Towards Generative Machine Teaching Technical University of Munich, Germany, February 2023 (mastersthesis)

ArchiSound: Audio Generation with Diffusion

Schneider, F.

ETH Zurich, Switzerland, January 2023, external supervision (mastersthesis)

ei Schneider, F. ArchiSound: Audio Generation with Diffusion ETH Zurich, Switzerland, January 2023, external supervision (mastersthesis)

Generation and Quantification of Spin in Robot Table Tennis

Dittrich, A.

University of Stuttgart, Germany, January 2023 (mastersthesis)

ei Dittrich, A. Generation and Quantification of Spin in Robot Table Tennis University of Stuttgart, Germany, January 2023 (mastersthesis)

Natural Language Processing for Policymaking

Jin, Z., Mihalcea, R.

In Handbook of Computational Social Science for Policy, pages: 141-162, 7, (Editors: Bertoni, E. and Fontana, M. and Gabrielli, L. and Signorelli, S. and Vespe, M.), Springer International Publishing, 2023 (inbook)

ei Jin, Z., Mihalcea, R. Natural Language Processing for Policymaking In Handbook of Computational Social Science for Policy, pages: 141-162, 7, (Editors: Bertoni, E. and Fontana, M. and Gabrielli, L. and Signorelli, S. and Vespe, M.), Springer International Publishing, 2023 (inbook)

2022

Magnetic Micro-/Nanopropellers for Biomedicine

Qiu, T., Jeong, M., Goyal, R., Kadiri, V., Sachs, J., Fischer, P.

In Field-Driven Micro and Nanorobots for Biology and Medicine, pages: 389-410, 16, (Editors: Sun, Y. and Wang, X. and Yu, J.), Springer, Cham, 2022 (inbook)

Abstract

In nature, many bacteria swim by rotating their helical flagella. A particularly promising class of artificial micro- and nano-robots mimic this propeller-like propulsion mechanism to move through fluids and tissues for applications in minimally-invasive medicine. Several fundamental challenges have to be overcome in order to build micro-machines that move similar to bacteria for in vivo applications. Here, we review recent advances of magnetically-powered micro-/nano-propellers. Four important aspects of the propellers – the geometrical shape, the fabrication method, the generation of magnetic fields for actuation, and the choice of biocompatible magnetic materials – are highlighted. First, the fundamental requirements are elucidated that arise due to hydrodynamics at low Reynolds (Re) number. We discuss the role that the propellers’ shape and symmetry play in realizing effective propulsion at low Re. Second, the additive nano-fabrication method Glancing Angle Deposition is discussed as a versatile technique to quickly grow large numbers of designer nano-helices. Third, systems to generate rotating magnetic fields via permanent magnets or electromagnetic coils are presented. And finally, the biocompatibility of the magnetic materials is discussed. Iron-platinum is highlighted due to its biocompatibility and its superior magnetic properties, which is promising for targeted delivery, minimally-invasive magnetic nano-devices and biomedical applications.

2022

pf Qiu, T., Jeong, M., Goyal, R., Kadiri, V., Sachs, J., Fischer, P. Magnetic Micro-/Nanopropellers for Biomedicine In Field-Driven Micro and Nanorobots for Biology and Medicine, pages: 389-410, 16, (Editors: Sun, Y. and Wang, X. and Yu, J.), Springer, Cham, 2022 (inbook)

Life Improvement Science

Lieder, F., Prentice, M.

In Encyclopedia of Quality of Life and Well-Being Research, Springer, November 2022 (inbook)

re Lieder, F., Prentice, M. Life Improvement Science In Encyclopedia of Quality of Life and Well-Being Research, Springer, November 2022 (inbook)

Investigating Independent Mechanisms in Neural Networks

Liang, W.

Université Paris-Saclay, France, October 2022 (mastersthesis)

ei Liang, W. Investigating Independent Mechanisms in Neural Networks Université Paris-Saclay, France, October 2022 (mastersthesis)

Modeling subgroup differences in fMRI data: disentangling subgroup-specific responses from shared ones

Keidar, D.

ETH Zurich, Switzerland, October 2022 (mastersthesis)

ei Keidar, D. Modeling subgroup differences in fMRI data: disentangling subgroup-specific responses from shared ones ETH Zurich, Switzerland, October 2022 (mastersthesis)

Multi-Target Multi-Object Manipulation using Relational Deep Reinforcement Learning

Feil, M.

Technnical University Munich, Germany, September 2022 (mastersthesis)

ei Feil, M. Multi-Target Multi-Object Manipulation using Relational Deep Reinforcement Learning Technnical University Munich, Germany, September 2022 (mastersthesis)

Independent Mechanism Analysis for High Dimensions

Sliwa, J.

University of Tübingen, Germany, September 2022, (Graduate Training Centre of Neuroscience) (mastersthesis)

ei Sliwa, J. Independent Mechanism Analysis for High Dimensions University of Tübingen, Germany, September 2022, (Graduate Training Centre of Neuroscience) (mastersthesis)

Patterns, Predictions, and Actions: Foundations of Machine Learning

Hardt, M., Recht, B.

Princeton University Press, August 2022 (book)

Abstract

An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impacts Patterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions. Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actions Pays special attention to societal impacts and fairness in decision making Traces the development of machine learning from its origins to today Features a novel chapter on machine learning benchmarks and datasets Invites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebra An essential textbook for students and a guide for researchers

sf Hardt, M., Recht, B. Patterns, Predictions, and Actions: Foundations of Machine Learning Princeton University Press, August 2022 (book)

On the Adversarial Robustness of Causal Algorithmic Recourse

Dominguez-Olmedo, R.

University of Tübingen, Germany, August 2022 (mastersthesis)

ei Dominguez-Olmedo, R. On the Adversarial Robustness of Causal Algorithmic Recourse University of Tübingen, Germany, August 2022 (mastersthesis)

Independent Mechanism Analysis in High-Dimensional Observation Spaces

Ghosh, S.

ETH Zurich, Switzerland, June 2022 (mastersthesis)

ei Ghosh, S. Independent Mechanism Analysis in High-Dimensional Observation Spaces ETH Zurich, Switzerland, June 2022 (mastersthesis)

Causal Models for Dynamical Systems

Peters, J., Bauer, S., Pfister, N.

In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 671-690, 1, Association for Computing Machinery, 2022 (inbook)

ei Peters, J., Bauer, S., Pfister, N. Causal Models for Dynamical Systems In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 671-690, 1, Association for Computing Machinery, 2022 (inbook)

Karimi, A. H., von Kügelgen, J., Schölkopf, B., Valera, I.

Towards Causal Algorithmic Recourse

In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 139-166, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

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ei plg Karimi, A. H., von Kügelgen, J., Schölkopf, B., Valera, I. Towards Causal Algorithmic Recourse In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 139-166, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations

Salewski, L., Koepke, A. S., Lensch, H. P. A., Akata, Z.

In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 69-88, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

ei Salewski, L., Koepke, A. S., Lensch, H. P. A., Akata, Z. CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 69-88, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

Causality for Machine Learning

Schölkopf, B.

In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 765-804, 1, Association for Computing Machinery, New York, NY, USA, 2022 (inbook)

ei Schölkopf, B. Causality for Machine Learning In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 765-804, 1, Association for Computing Machinery, New York, NY, USA, 2022 (inbook)

Voltage dependent investigations on the spin polarization of layered heterostructues

Miller, M.

Universität Stuttgart, Stuttgart, 2022 (mastersthesis)

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mms Miller, M. Voltage dependent investigations on the spin polarization of layered heterostructues Universität Stuttgart, Stuttgart, 2022 (mastersthesis)

2021

Learning Neural Causal Models with Active Interventions

Scherrer, N.

ETH Zurich, Switzerland, November 2021 (mastersthesis)

2021

ei Scherrer, N. Learning Neural Causal Models with Active Interventions ETH Zurich, Switzerland, November 2021 (mastersthesis)

HealthGen: Conditional Generation of Realistic Medical Time Series with Informative Missingness

Bing, S.

ETH Zurich, Switzerland, October 2021 (mastersthesis)

ei Bing, S. HealthGen: Conditional Generation of Realistic Medical Time Series with Informative Missingness ETH Zurich, Switzerland, October 2021 (mastersthesis)

Study of the Interventional Consistency of Autoencoders

Lanzillotta, G.

ETH Zurich, Switzerland, October 2021 (mastersthesis)

ei Lanzillotta, G. Study of the Interventional Consistency of Autoencoders ETH Zurich, Switzerland, October 2021 (mastersthesis)

Training with Few to Manipulate Many. On OOD generalization in relational reinforcement learning

Mambelli, D.

ETH Zurich, Switzerland, October 2021 (mastersthesis)

ei Mambelli, D. Training with Few to Manipulate Many. On OOD generalization in relational reinforcement learning ETH Zurich, Switzerland, October 2021 (mastersthesis)

Supplemental Material link (url) DOI [BibTex]

Electriflow: Augmenting Books With Tangible Animation Using Soft Electrohydraulic Actuators

Purnendu, , Novack, S., Acome, E., Alistar, M., Keplinger, C., Gross, M. D., Bruns, C., Leithinger, D.

In ACM SIGGRAPH 2021 Labs, pages: 1-2, Association for Computing Machinery, SIGGRAPH 2021, August 2021 (inbook)

Abstract

We present Electriflow: a method of augmenting books with tangible animation employing soft electrohydraulic actuators. These actuators are compact, silent and fast in operation, and can be fabricated with commodity materials. They generate an immediate hydraulic force upon electrostatic activation without an external fluid supply source, enabling a simple and self-contained design. Electriflow actuators produce an immediate shape transition from flat to folded state which enabled their seamless integration into books. For the Emerging Technologies exhibit, we will demonstrate the prototype of a book augmented with the capability of tangible animation.

rm Purnendu, , Novack, S., Acome, E., Alistar, M., Keplinger, C., Gross, M. D., Bruns, C., Leithinger, D. Electriflow: Augmenting Books With Tangible Animation Using Soft Electrohydraulic Actuators In ACM SIGGRAPH 2021 Labs, pages: 1-2, Association for Computing Machinery, SIGGRAPH 2021, August 2021 (inbook)

Supplemental Material link (url) DOI [BibTex]

Robotic Surgery Training in AR: Multimodal Record and Replay

Krauthausen, F.

pages: 1-147, University of Stuttgart, Stuttgart, May 2021, Study Program in Software Engineering (mastersthesis)

hi Krauthausen, F. Robotic Surgery Training in AR: Multimodal Record and Replay pages: 1-147, University of Stuttgart, Stuttgart, May 2021, Study Program in Software Engineering (mastersthesis)

Direct detection of spin Hall effect induced torques in platinum/ferromagnetic bilayer systems

Alten, F.

Universität Stuttgart, Stuttgart, January 2021 (mastersthesis)

mms

mms Alten, F. Direct detection of spin Hall effect induced torques in platinum/ferromagnetic bilayer systems Universität Stuttgart, Stuttgart, January 2021 (mastersthesis)

Sitti, M., Liimatainen, V.

Method of making one or more fibrils, computer implemented method of simulating an adhesive force of one or more fibrils and fibril

2021, EP Prio. Patent App. 21 162 253.5 (mpi_year_book)

pi Sitti, M., Liimatainen, V. Method of making one or more fibrils, computer implemented method of simulating an adhesive force of one or more fibrils and fibril 2021, EP Prio. Patent App. 21 162 253.5 (mpi_year_book)

Reinforcement Learning Algorithms: Analysis and Applications

Belousov, B., H., A., Klink, P., Parisi, S., Peters, J.

883, Studies in Computational Intelligence, Springer International Publishing, 2021 (book)

ei Belousov, B., H., A., Klink, P., Parisi, S., Peters, J. Reinforcement Learning Algorithms: Analysis and Applications 883, Studies in Computational Intelligence, Springer International Publishing, 2021 (book)

Community detection in heterogeneously attributed networks

Zottino, N.

Politecnico di Torino, 2021 (mastersthesis)

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pio Zottino, N. Community detection in heterogeneously attributed networks Politecnico di Torino, 2021 (mastersthesis)

Scientific Report 2016 - 2021 [BibTex]

Scientific Report 2016 - 2021

2021 (mpi_year_book)

Abstract

This report presents research done at the Max Planck Institute for Intelligent Systems from January2016 to November 2021. It is our fourth report since the founding of the institute in 2011. Dueto the fact that the upcoming evaluation is an extended one, the report covers a longer reportingperiod.This scientific report is organized as follows: we begin with an overview of the institute, includingan outline of its structure, an introduction of our latest research departments, and a presentationof our main collaborative initiatives and activities (Chapter1). The central part of the scientificreport consists of chapters on the research conducted by the institute’s departments (Chapters2to6) and its independent research groups (Chapters7 to24), as well as the work of the institute’scentral scientific facilities (Chapter25). For entities founded after January 2016, the respectivereport sections cover work done from the date of the establishment of the department, group, orfacility. These chapters are followed by a summary of selected outreach activities and scientificevents hosted by the institute (Chapter26). The scientific publications of the featured departmentsand research groups published during the 6-year review period complete this scientific report.

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ei hi ps pi rm Scientific Report 2016 - 2021 2021 (mpi_year_book)

Scientific Report 2016 - 2021 [BibTex]

2020

Hydromagnonics: Manipulation of magnonic systems with hydrogen

Sauter, R.

Universität Stuttgart, Stuttgart, December 2020 (mastersthesis)

mms

2020

mms Sauter, R. Hydromagnonics: Manipulation of magnonic systems with hydrogen Universität Stuttgart, Stuttgart, December 2020 (mastersthesis)

A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Ahmed, O.

ETH Zurich, Switzerland, October 2020 (mastersthesis)

ei Ahmed, O. A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning ETH Zurich, Switzerland, October 2020 (mastersthesis)

A Comprehensive Benchmark Evaluation of Synthetic Data Generation for Biomedical Imaging

DuMont Schütte, A.

ETH Zurich, Switzerland, October 2020 (mastersthesis)

ei DuMont Schütte, A. A Comprehensive Benchmark Evaluation of Synthetic Data Generation for Biomedical Imaging ETH Zurich, Switzerland, October 2020 (mastersthesis)

Deep learning for the parameter estimation of tight-binding Hamiltonians

Cacioppo, A.

University of Roma, La Sapienza, Italy, May 2020 (mastersthesis)

ei Cacioppo, A. Deep learning for the parameter estimation of tight-binding Hamiltonians University of Roma, La Sapienza, Italy, May 2020 (mastersthesis)

Learning Algorithms, Invariances, and the Real World

Zecevic, M.

Technical University of Darmstadt, Germany, April 2020 (mastersthesis)

ei Zecevic, M. Learning Algorithms, Invariances, and the Real World Technical University of Darmstadt, Germany, April 2020 (mastersthesis)

Interaction of hydrogen isotopes with flexible metal-organic frameworks

Bondorf, L.

Universität Stuttgart, Stuttgart, February 2020 (mastersthesis)

mms

mms Bondorf, L. Interaction of hydrogen isotopes with flexible metal-organic frameworks Universität Stuttgart, Stuttgart, February 2020 (mastersthesis)

Developing new methods for routing and optimal transport on networks

Lonardi, A.

Università degli studi di Padova, 2020 (mastersthesis)

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pdf [BibTex]

pio Lonardi, A. Developing new methods for routing and optimal transport on networks Università degli studi di Padova, 2020 (mastersthesis)

pdf [BibTex]

TUM Flyers: Vision-Based MAV Navigation for Systematic Inspection of Structures

Usenko, V., Stumberg, L. V., Stückler, J., Cremers, D.

In Bringing Innovative Robotic Technologies from Research Labs to Industrial End-users: The Experience of the European Robotics Challenges, 136, pages: 189-209, Springer Tracts in Advanced Robotics, Springer International Publishing, 2020 (inbook)

ev Usenko, V., Stumberg, L. V., Stückler, J., Cremers, D. TUM Flyers: Vision-Based MAV Navigation for Systematic Inspection of Structures In Bringing Innovative Robotic Technologies from Research Labs to Industrial End-users: The Experience of the European Robotics Challenges, 136, pages: 189-209, Springer Tracts in Advanced Robotics, Springer International Publishing, 2020 (inbook)

Edge-Disjoint Path Problem on Stochastic Block Models through Message Passing

Lorenzo Ferretti

Sapienza Università di Roma, 2020 (mastersthesis)

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pio Lorenzo Ferretti Edge-Disjoint Path Problem on Stochastic Block Models through Message Passing Sapienza Università di Roma, 2020 (mastersthesis)

Popescu, M. N., Uspal, W. E.

Adopting the Boundary Homogenization Approximation from Chemical Kinetics to Motile Chemically Active Particles

In Chemical Kinetics, pages: 517-540, (Editors: Lindenberg, Katja and Metzler, Ralf and Oshanin, Gleb), World Scientific, New Jersey, NJ, 2020 (incollection)

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icm Popescu, M. N., Uspal, W. E. Adopting the Boundary Homogenization Approximation from Chemical Kinetics to Motile Chemically Active Particles In Chemical Kinetics, pages: 517-540, (Editors: Lindenberg, Katja and Metzler, Ralf and Oshanin, Gleb), World Scientific, New Jersey, NJ, 2020 (incollection)

Colloidal particles supporting urase activity

Baldauf, A.

Univ. of Stuttgart, 2020 (mastersthesis)

pf Baldauf, A. Colloidal particles supporting urase activity Univ. of Stuttgart, 2020 (mastersthesis)

Soft Microrobots Based on Photoresponsive Materials

Palagi, S.

In Mechanically Responsive Materials for Soft Robotics, pages: 327-362, (Editors: Koshima, Hideko), Wiley-VCH, Weinheim, 2020 (incollection)

pf Palagi, S. Soft Microrobots Based on Photoresponsive Materials In Mechanically Responsive Materials for Soft Robotics, pages: 327-362, (Editors: Koshima, Hideko), Wiley-VCH, Weinheim, 2020 (incollection)

Diffusion studies on biomolecules by NMR

Bochert, I.

Univ. of Stuttgart, 2020 (mastersthesis)

pf Bochert, I. Diffusion studies on biomolecules by NMR Univ. of Stuttgart, 2020 (mastersthesis)

Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art

Janai, J., Güney, F., Behl, A., Geiger, A.

12(1-3), Foundations and Trends® in Computer Graphics and Vision, now Publishers Inc., Hanover, MA, 2020 (book)

Abstract

Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it becomes increasingly difficult to stay up-to-date or enter the field as a beginner. While several survey papers on particular sub-problems have appeared, no comprehensive survey on problems, datasets, and methods in computer vision for autonomous vehicles has been published. This monograph attempts to narrow this gap by providing a survey on the state-of-the-art datasets and techniques. Our survey includes both the historically most relevant literature as well as the current state of the art on several specific topics, including recognition, reconstruction, motion estimation, tracking, scene understanding, and end-to-end learning for autonomous driving. Towards this goal, we analyze the performance of the state of the art on several challenging benchmarking datasets, including KITTI, MOT, and Cityscapes. Besides, we discuss open problems and current research challenges. To ease accessibility and accommodate missing references, we also provide a website that allows navigating topics as well as methods and provides additional information.

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pdf Project Page link DOI Project Page [BibTex]

avg Janai, J., Güney, F., Behl, A., Geiger, A. Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art 12(1-3), Foundations and Trends® in Computer Graphics and Vision, now Publishers Inc., Hanover, MA, 2020 (book)

pdf Project Page link DOI Project Page [BibTex]

2019

Analysis and modelling of information ecosystems

Emanuele Pigani

Università degli studi di Padova, October 2019 (mastersthesis)

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2019

pio Emanuele Pigani Analysis and modelling of information ecosystems Università degli studi di Padova, October 2019 (mastersthesis)