Gabriele Scalia

Orcid: 0000-0003-3305-9220

According to our database1, Gabriele Scalia authored at least 28 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Adding Conditional Control to Diffusion Models with Reinforcement Learning.
CoRR, 2024

Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models.
CoRR, 2024

Feedback Efficient Online Fine-Tuning of Diffusion Models.
CoRR, 2024

Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control.
CoRR, 2024

Conformalized Deep Splines for Optimal and Efficient Prediction Sets.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Complex Preferences for Different Convergent Priors in Discrete Graph Diffusion.
CoRR, 2023

RINGER: Rapid Conformer Generation for Macrocycles with Sequence-Conditioned Internal Coordinate Diffusion.
CoRR, 2023

GraphGUIDE: interpretable and controllable conditional graph generation with discrete Bernoulli diffusion.
CoRR, 2023

Improving Graph Generation by Restricting Graph Bandwidth.
Proceedings of the International Conference on Machine Learning, 2023

2022
CIME: Context-aware geolocation of emergency-related posts.
GeoInformatica, 2022

Hierarchically branched diffusion models for efficient and interpretable multi-class conditional generation.
CoRR, 2022

A 3D-Shape Similarity-based Contrastive Approach to Molecular Representation Learning.
CoRR, 2022

Conditional Diffusion with Less Explicit Guidance via Model Predictive Control.
CoRR, 2022

Hybrid deep learning-based feature-augmented detection for molecular communication systems.
Proceedings of the NANOCOM '22: The Ninth Annual ACM International Conference on Nanoscale Computing and Communication, Barcelona, Catalunya, Spain, October 5, 2022

2021
Machine learning-driven integration, knowledge extraction and uncertainty management for scientific data.
PhD thesis, 2021

Data Ecosystems for Scientific Experiments: Managing Combustion Experiments and Simulation Analyses in Chemical Engineering.
Frontiers Big Data, 2021

Image-Based Social Sensing: Combining AI and the Crowd to Mine Policy-Adherence Indicators from Twitter.
Proceedings of the 43rd IEEE/ACM International Conference on Software Engineering: Software Engineering in Society, 2021

About the Quality of Data and Services in Natural Sciences.
Proceedings of the Next-Gen Digital Services. A Retrospective and Roadmap for Service Computing of the Future, 2021

2020
Evaluating Scalable Uncertainty Estimation Methods for Deep Learning-Based Molecular Property Prediction.
J. Chem. Inf. Model., 2020

A Data-driven Approach to Optimize Bounds on the Capacity of the Molecular Channel.
Proceedings of the IEEE Global Communications Conference, 2020

2019
Spatio-temporal mining of keywords for social media cross-social crawling of emergency events.
GeoInformatica, 2019

Towards a scientific data framework to support scientific model development.
Data Sci., 2019

Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction.
CoRR, 2019

2018
Geolocating social media posts for emergency mapping.
CoRR, 2018

Storing Combustion Data Experiments: New Requirements Emerging from a First Prototype - Position Paper.
Proceedings of the Semantics, Analytics, Visualization, 2018

2017
E2mC: Improving Emergency Management Service Practice through Social Media and Crowdsourcing Analysis in Near Real Time.
Sensors, 2017

Exploratory Spatio-Temporal Queries in Evolving Information.
Proceedings of the Mobility Analytics for Spatio-Temporal and Social Data, 2017

IMEXT: A method and system to extract geolocated images from Tweets - Analysis of a case study.
Proceedings of the 11th International Conference on Research Challenges in Information Science, 2017


  Loading...