IMEXT: A method and system to extract geolocated images from Tweets - Analysis of a case study. - Chiara Francalanci; Paolo Guglielmino; Matteo Montalcini; Gabriele Scalia; Barbara Pernici (RCIS, 2017)

Exploratory Spatio-Temporal Queries in Evolving Information. - Chiara Francalanci; Barbara Pernici; Gabriele Scalia (MATES@VLDB, 2017)

E2mC: Improving Emergency Management Service Practice through Social Media and Crowdsourcing Analysis in Near Real Time. - Clemens Havas; Bernd Resch; Chiara Francalanci; Barbara Pernici; Gabriele Scalia; Jose Luis Fernandez-Marquez; Tim Van Achte; Gunter Zeug; Maria Rosa (Rosy) Mondardini; Domenico Grandoni; Birgit Kirsch; Milan Kalas; et al. (Sensors, 2017)

Storing Combustion Data Experiments: New Requirements Emerging from a First Prototype - Position Paper. - Gabriele Scalia; Matteo Pelucchi; Alessandro Stagni; Tiziano Faravelli; Barbara Pernici (SAVE-SD@WWW, 2018)

Geolocating social media posts for emergency mapping. - Barbara Pernici; Chiara Francalanci; Gabriele Scalia; Marco Corsi; Domenico Grandoni; Mariano Alfonso Biscardi (CoRR, 2018)

Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction. - Gabriele Scalia; Colin A. Grambow; Barbara Pernici; Yi-Pei Li; William H. Green Jr. (CoRR, 2019)

Towards a scientific data framework to support scientific model development. - Gabriele Scalia; Matteo Pelucchi; Alessandro Stagni; Alberto Cuoci; Tiziano Faravelli; Barbara Pernici (Data Sci., 2019)

Spatio-temporal mining of keywords for social media cross-social crawling of emergency events. - Andrea Autelitano; Barbara Pernici; Gabriele Scalia (GeoInformatica, 2019)

A Data-driven Approach to Optimize Bounds on the Capacity of the Molecular Channel. - Francesca Ratti; Gabriele Scalia; Barbara Pernici; Maurizio Magarini (GLOBECOM, 2020)

Evaluating Scalable Uncertainty Estimation Methods for Deep Learning-Based Molecular Property Prediction. - Gabriele Scalia; Colin A. Grambow; Barbara Pernici; Yi-Pei Li; William H. Green Jr. (J. Chem. Inf. Model., 2020)

About the Quality of Data and Services in Natural Sciences. - Barbara Pernici; Francesca Ratti; Gabriele Scalia (Next-Gen Digital Services, 2021)

Image-Based Social Sensing: Combining AI and the Crowd to Mine Policy-Adherence Indicators from Twitter. - Virginia Negri; Dario Scuratti; Stefano Agresti; Donya Rooein; Gabriele Scalia; Amudha Ravi Shankar; Jose Luis Fernandez-Marquez; Mark James Carman; Barbara Pernici (ICSE-SEIS, 2021)

Data Ecosystems for Scientific Experiments: Managing Combustion Experiments and Simulation Analyses in Chemical Engineering. - Edoardo Ramalli; Gabriele Scalia; Barbara Pernici; Alessandro Stagni; Alberto Cuoci; Tiziano Faravelli (Frontiers Big Data, 2021)

Machine learning-driven integration, knowledge extraction and uncertainty management for scientific data. - Gabriele Scalia (2021)

Hybrid deep learning-based feature-augmented detection for molecular communication systems. - Fardad Vakilipoor; Davide Scazzoli; Francesca Ratti; Gabriele Scalia; Maurizio Magarini (NANOCOM, 2022)

Conditional Diffusion with Less Explicit Guidance via Model Predictive Control. - Max W. Shen; Ehsan Hajiramezanali; Gabriele Scalia; Alex M. Tseng; Nathaniel Diamant; Tommaso Biancalani; Andreas Loukas (CoRR, 2022)

A 3D-Shape Similarity-based Contrastive Approach to Molecular Representation Learning. - Austin Atsango; Nathaniel L. Diamant; Ziqing Lu; Tommaso Biancalani; Gabriele Scalia; Kangway V. Chuang (CoRR, 2022)

Hierarchically branched diffusion models for efficient and interpretable multi-class conditional generation. - Alex M. Tseng; Tommaso Biancalani; Max W. Shen; Gabriele Scalia (CoRR, 2022)

CIME: Context-aware geolocation of emergency-related posts. - Gabriele Scalia; Chiara Francalanci; Barbara Pernici (GeoInformatica, 2022)

Improving Graph Generation by Restricting Graph Bandwidth. - Nathaniel Lee Diamant; Alex M. Tseng; Kangway V. Chuang; Tommaso Biancalani; Gabriele Scalia (ICML, 2023)

GraphGUIDE: interpretable and controllable conditional graph generation with discrete Bernoulli diffusion. - Alex M. Tseng; Nathaniel Diamant; Tommaso Biancalani; Gabriele Scalia (CoRR, 2023)

RINGER: Rapid Conformer Generation for Macrocycles with Sequence-Conditioned Internal Coordinate Diffusion. - Colin A. Grambow; Hayley Weir; Nathaniel L. Diamant; Alex M. Tseng; Tommaso Biancalani; Gabriele Scalia; Kangway V. Chuang (CoRR, 2023)

Complex Preferences for Different Convergent Priors in Discrete Graph Diffusion. - Alex M. Tseng; Nathaniel Diamant; Tommaso Biancalani; Gabriele Scalia (CoRR, 2023)

Conformalized Deep Splines for Optimal and Efficient Prediction Sets. - Nathaniel Diamant; Ehsan Hajiramezanali; Tommaso Biancalani; Gabriele Scalia (AISTATS, 2024)

Feedback Efficient Online Fine-Tuning of Diffusion Models. - Masatoshi Uehara; Yulai Zhao 002; Kevin Black; Ehsan Hajiramezanali; Gabriele Scalia; Nathaniel Lee Diamant; Alex M. Tseng; Sergey Levine; Tommaso Biancalani (ICML, 2024)

GFlowNet Assisted Biological Sequence Editing. - Pouya M. Ghari; Alex M. Tseng; Gökcen Eraslan; Romain Lopez; Tommaso Biancalani; Gabriele Scalia; Ehsan Hajiramezanali (NeurIPS, 2024)

Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models. - Masatoshi Uehara; Yulai Zhao 002; Ehsan Hajiramezanali; Gabriele Scalia; Gökcen Eraslan; Avantika Lal; Sergey Levine; Tommaso Biancalani (NeurIPS, 2024)

Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control. - Masatoshi Uehara; Yulai Zhao 002; Kevin Black; Ehsan Hajiramezanali; Gabriele Scalia; Nathaniel Lee Diamant; Alex M. Tseng; Tommaso Biancalani; Sergey Levine (CoRR, 2024)

Adding Conditional Control to Diffusion Models with Reinforcement Learning. - Yulai Zhao 002; Masatoshi Uehara; Gabriele Scalia; Tommaso Biancalani; Sergey Levine; Ehsan Hajiramezanali (CoRR, 2024)

Cell Morphology-Guided Small Molecule Generation with GFlowNets. - Stephen Zhewen Lu; Ziqing Lu; Ehsan Hajiramezanali; Tommaso Biancalani; Yoshua Bengio; Gabriele Scalia; Michal Koziarski (CoRR, 2024)

Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding. - Xiner Li; Yulai Zhao 002; Chenyu Wang 003; Gabriele Scalia; Gökcen Eraslan; Surag Nair; Tommaso Biancalani; Aviv Regev; Sergey Levine; Masatoshi Uehara (CoRR, 2024)

A mechanistically interpretable neural network for regulatory genomics. - Alex M. Tseng; Gökcen Eraslan; Tommaso Biancalani; Gabriele Scalia (CoRR, 2024)

MolCap-Arena: A Comprehensive Captioning Benchmark on Language-Enhanced Molecular Property Prediction. - Carl Edwards; Ziqing Lu; Ehsan Hajiramezanali; Tommaso Biancalani; Heng Ji; Gabriele Scalia (CoRR, 2024)

Efficient Fine-Tuning of Single-Cell Foundation Models Enables Zero-Shot Molecular Perturbation Prediction. - Sepideh Maleki; Jan-Christian Huetter; Kangway V. Chuang; Gabriele Scalia; Tommaso Biancalani (CoRR, 2024)

Score-based Explainability for Graph Representations. - Ehsan Hajiramezanali; Sepideh Maleki; Max W. Shen; Kangway V. Chuang; Tommaso Biancalani; Gabriele Scalia (Trans. Mach. Learn. Res., 2024)

Hierarchically branched diffusion models leverage dataset structure for class-conditional generation. - Alex M. Tseng; Max W. Shen; Tommaso Biancalani; Gabriele Scalia (Trans. Mach. Learn. Res., 2024)

Adding Conditional Control to Diffusion Models with Reinforcement Learning. - Yulai Zhao 002; Masatoshi Uehara; Gabriele Scalia; Sun-Yuan Kung; Tommaso Biancalani; Sergey Levine; Ehsan Hajiramezanali (ICLR, 2025)

Learning Multi-cellular Representations of Single-Cell Transcriptomics Data Enables Characterization of Patient-Level Disease States. - Tianyu Liu 001; Edward De Brouwer; Tony Kuo; Nathaniel Diamant; Alsu Missarova; Hanchen Wang 002; Minsheng Hao; Héctor Corrada Bravo; Gabriele Scalia; Aviv Regev; Graham Heimberg (RECOMB, 2025)

RAG-Enhanced Collaborative LLM Agents for Drug Discovery. - Namkyeong Lee; Edward De Brouwer; Ehsan Hajiramezanali; Chanyoung Park 001; Gabriele Scalia (CoRR, 2025)

Dynamic Search for Inference-Time Alignment in Diffusion Models. - Xiner Li; Masatoshi Uehara; Xingyu Su; Gabriele Scalia; Tommaso Biancalani; Aviv Regev; Sergey Levine; Shuiwang Ji (CoRR, 2025)

Iterative Distillation for Reward-Guided Fine-Tuning of Diffusion Models in Biomolecular Design. - Xingyu Su; Xiner Li; Masatoshi Uehara; Sunwoo Kim; Yulai Zhao 002; Gabriele Scalia; Ehsan Hajiramezanali; Tommaso Biancalani; Degui Zhi; Shuiwang Ji (CoRR, 2025)