An ALE-based numerical technique for modeling sedimentary basin evolution featuring layer deformations and faults. - Matteo Longoni; A. Cristiano I. Malossi; Alfio Quarteroni; Andrea Villa; Paolo Ruffo (J. Comput. Phys., 2011)

On the continuity of mean total normal stress in geometrical multiscale cardiovascular problems. - Pablo J. Blanco; Simone Deparis; A. Cristiano I. Malossi (J. Comput. Phys., 2013)

Implicit Coupling of One-Dimensional and Three-Dimensional Blood Flow Models with Compliant Vessels. - A. Cristiano I. Malossi; Pablo J. Blanco; Paolo Crosetto; Simone Deparis; Alfio Quarteroni (Multiscale Model. Simul., 2013)

Performance and Energy-Aware Characterization of the Sparse Matrix-Vector Multiplication on Multithreaded Architectures. - A. Cristiano I. Malossi; Yves Ineichen; Constantine Bekas; Alessandro Curioni; Enrique S. Quintana-Ortí (ICPP Workshops, 2014)

Changing Computing Paradigms Towards Power Efficiency. - Pavel Klavík; A. Cristiano I. Malossi; Constantine Bekas; Alessandro Curioni (CoRR, 2014)

An extreme-scale implicit solver for complex PDEs: highly heterogeneous flow in earth's mantle. - Johann Rudi; A. Cristiano I. Malossi; Tobin Isaac; Georg Stadler; Michael Gurnis; Peter W. J. Staar; Yves Ineichen; Costas Bekas; Alessandro Curioni; Omar Ghattas (SC, 2015)

Systematic derivation of time and power models for linear algebra kernels on multicore architectures. - A. Cristiano I. Malossi; Yves Ineichen; Costas Bekas; Alessandro Curioni; Enrique S. Quintana-Ortí (Sustain. Comput. Informatics Syst., 2015)

The Impact of Voltage-Frequency Scaling for the Matrix-Vector Product on the IBM POWER8. - Sandra Catalán; A. Cristiano I. Malossi; Costas Bekas; Enrique S. Quintana-Ortí (Euro-Par, 2016)

Stochastic Matrix-Function Estimators: Scalable Big-Data Kernels with High Performance. - Peter W. J. Staar; Panagiotis Kl. Barkoutsos; Roxana Istrate; A. Cristiano I. Malossi; Ivano Tavernelli; Nikolaj Moll; Heiner Giefers; Christoph Hagleitner; Costas Bekas; Alessandro Curioni (IPDPS, 2016)

First Experiences with ab initio Molecular Dynamics on OpenPOWER: The Case of CPMD. - Valéry Weber; A. Cristiano I. Malossi; Ivano Tavernelli; Teodoro Laino; Costas Bekas; Manish Modani; Nina Wilner; Tom Heller; Alessandro Curioni (ISC Workshops, 2016)

Impact of temporal subsampling on accuracy and performance in practical video classification. - Florian Scheidegger; Lukas Cavigelli; Michael Schaffner; A. Cristiano I. Malossi; Constantine Bekas; Luca Benini (EUSIPCO, 2017)

Incremental Training of Deep Convolutional Neural Networks. - Roxana Istrate; A. Cristiano I. Malossi; Costas Bekas; Dimitrios S. Nikolopoulos (AutoML@PKDD/ECML, 2017)

The transprecision computing paradigm: Concept, design, and applications. - A. Cristiano I. Malossi; Michael Schaffner; Anca Molnos; Luca Gammaitoni; Giuseppe Tagliavini; Andrew P. J. Emerson; Andrés Tomás; Dimitrios S. Nikolopoulos; Eric Flamand; Norbert Wehn (DATE, 2018)

BAGAN: Data Augmentation with Balancing GAN. - Giovanni Mariani; Florian Scheidegger; Roxana Istrate; Costas Bekas; A. Cristiano I. Malossi (CoRR, 2018)

A scalable iterative dense linear system solver for multiple right-hand sides in data analytics. - Vassilis Kalantzis; A. Cristiano I. Malossi; Costas Bekas; Alessandro Curioni; Efstratios Gallopoulos; Yousef Saad (Parallel Comput., 2018)

TAPAS: Train-Less Accuracy Predictor for Architecture Search. - Roxana Istrate; Florian Scheidegger; Giovanni Mariani; Dimitrios S. Nikolopoulos; Constantine Bekas; Adelmo Cristiano Innocenza Malossi (AAAI, 2019)

Constrained deep neural network architecture search for IoT devices accounting for hardware calibration. - Florian Scheidegger; Luca Benini; Costas Bekas; A. Cristiano I. Malossi (NeurIPS, 2019)

NeuNetS: An Automated Synthesis Engine for Neural Network Design. - Atin Sood; Benjamin Elder; Benjamin Herta; Chao Xue; Costas Bekas; A. Cristiano I. Malossi; Debashish Saha; Florian Scheidegger; Ganesh Venkataraman; Gegi Thomas; Giovanni Mariani; Hendrik Strobelt; et al. (CoRR, 2019)

FloatX: A C++ Library for Customized Floating-Point Arithmetic. - Goran Flegar; Florian Scheidegger; Vedran Novakovic; Giovanni Mariani; Andrés E. Tomás; A. Cristiano I. Malossi; Enrique S. Quintana-Ortí (ACM Trans. Math. Softw., 2019)

XwattPilot: A Full-stack Cloud System Enabling Agile Development of Transprecision Software for Low-power SoCs. - Dionysios Diamantopoulos; Florian Scheidegger; Stefan Mach; Fabian Schuiki; Germain Haugou; Michael Schaffner; Frank K. Gürkaynak; Christoph Hagleitner; A. Cristiano I. Malossi; Luca Benini (COOL CHIPS, 2020)

Reducing Data Motion to Accelerate the Training of Deep Neural Networks. - Sicong Zhuang; A. Cristiano I. Malossi; Marc Casas (CoRR, 2020)

Generating Efficient DNN-Ensembles with Evolutionary Computation. - Marc Ortiz; Florian Scheidegger; Marc Casas; A. Cristiano I. Malossi; Eduard Ayguadé (CoRR, 2020)

torcpy: Supporting task parallelism in Python. - Panagiotis E. Hadjidoukas; Andrea Bartezzaghi; Florian Scheidegger; Roxana Istrate; Costas Bekas; A. Cristiano I. Malossi (SoftwareX, 2020)

AutoText: An End-to-End AutoAI Framework for Text. - Arunima Chaudhary; Alayt Issak; Kiran Kate; Yannis Katsis; Abel N. Valente; Dakuo Wang; Alexandre V. Evfimievski; Sairam Gurajada; Ban Kawas; A. Cristiano I. Malossi; Lucian Popa 001; Tejaswini Pedapati; et al. (AAAI, 2021)

Efficient image dataset classification difficulty estimation for predicting deep-learning accuracy. - Florian Scheidegger; Roxana Istrate; Giovanni Mariani; Luca Benini; Costas Bekas; A. Cristiano I. Malossi (Vis. Comput., 2021)

Active Learning for Imbalanced Civil Infrastructure Data. - Thomas Frick; Diego Antognini; Mattia Rigotti; Ioana Giurgiu; Benjamin F. Grewe; Cristiano Malossi (ECCV Workshops (7), 2022)

Model-Assisted Labeling via Explainability for Visual Inspection of Civil Infrastructures. - Klára Janousková; Mattia Rigotti; Ioana Giurgiu; Cristiano Malossi (ECCV Workshops (7), 2022)

Diagnostic Accuracy and Reliability of Deep Learning-Based Human Papillomavirus Status Prediction in Oropharyngeal Cancer. - Agustina La Greca Saint-Esteven; Chiara Marchiori; Marta Bogowicz; Javier Barranco Garcia; Zahra Khodabakhshi; Ender Konukoglu; Oliver Riesterer; Panagiotis Balermpas; Martin Hüllner; A. Cristiano I. Malossi; Matthias Guckenberger; Janita E. van Timmeren; et al. (MICAD, 2022)

Enabling Reproducibility and Meta-learning Through a Lifelong Database of Experiments (LDE). - Jason Tsay; Andrea Bartezzaghi; Aleke Nolte; A. Cristiano I. Malossi (CoRR, 2022)

Improving Low-Resource Question Answering using Active Learning in Multiple Stages. - Maximilian Schmidt; Andrea Bartezzaghi; Jasmina Bogojeska; A. Cristiano I. Malossi; Thang Vu (CoRR, 2022)

Counterfactual Image Generation for adversarially robust and interpretable Classifiers. - Rafael Bischof; Florian Scheidegger; Michael A. Kraus; A. Cristiano I. Malossi (CoRR, 2023)

Beyond Static and Dynamic Quantization - Hybrid Quantization of Vision Transformers. - Piotr Kluska; Florian Scheidegger; A. Cristiano I. Malossi; Enrique S. Quintana-Ortí (BMVC, 2024)

QAttn: Efficient GPU Kernels for mixed-precision Vision Transformers. - Piotr Kluska; Adrián Castelló 001; Florian Scheidegger; A. Cristiano I. Malossi; Enrique S. Quintana-Ortí (CVPR Workshops, 2024)

Combining Data Generation and Active Learning for Low-Resource Question Answering. - Maximilian Kimmich; Andrea Bartezzaghi; Jasmina Bogojeska; Cristiano Malossi; Ngoc Thang Vu (ICANN (7), 2024)

Probabilistic Feature Matching for Fast Scalable Visual Prompting. - Thomas Frick; Cezary Skura; Filip Janicki; Roy Assaf; Niccolò Avogaro; Daniel Caraballo; Yagmur Gizem Cinar; Brown Ebouky; Ioana Giurgiu; Takayuki Katsuki; Piotr Kluska; Cristiano Malossi; et al. (IJCAI, 2024)

Outline-Guided Object Inpainting with Diffusion Models. - Markus Pobitzer; Filip Janicki; Mattia Rigotti; Cristiano Malossi (CoRR, 2024)

MC Layer Normalization for calibrated uncertainty in Deep Learning. - Thomas Frick; Diego Antognini; Ioana Giurgiu; Benjamin F. Grewe; Cristiano Malossi; Rong J. B. Zhu; Mattia Rigotti (Trans. Mach. Learn. Res., 2024)

Show or Tell? Effectively prompting Vision-Language Models for semantic segmentation. - Niccolò Avogaro; Thomas Frick; Mattia Rigotti; Andrea Bartezzaghi; Filip Janicki; A. Cristiano I. Malossi; Konrad Schindler; Roy Assaf (Trans. Mach. Learn. Res., 2025)

VP Lab: a PEFT-Enabled Visual Prompting Laboratory for Semantic Segmentation. - Niccolò Avogaro; Thomas Frick; Yagmur Gizem Cinar; Daniel Caraballo; Cezary Skura; Filip Janicki; Piotr Kluska; Brown Ebouky; Nicola Farronato; Florian Scheidegger; Cristiano Malossi; Konrad Schindler; et al. (CoRR, 2025)

Q-SAM2: Accurate Quantization for Segment Anything Model 2. - Nicola Farronato; Florian Scheidegger; Mattia Rigotti; Cristiano Malossi; Michele Magno; Haotong Qin (CoRR, 2025)