Gianni Franchi
16 papers · 2020–2026 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+3 more ↓ Show less ↑
🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (36) 🌍 Conference Polyglot · Silver 🗃️ Keyword Collector (61)
🔥
Unstoppable · Bronze
⚡
Prolific Year · Productive
💎
Century Club · Bronze
Top co-authors
Research topics
Deep Learning
(11)
Machine Learning
(10)
Artificial Intelligence
(9)
Core AI
(6)
Optimization & Theory
(6)
Architectures
(5)
Bayesian & Probabilistic
(4)
Learning Types · Machine Learning
(4)
Computer Vision
(3)
Application Areas
(3)
Core Methods
(3)
Learning Types · Deep Learning
(3)
Analysis
(2)
Models
(2)
Techniques
(2)
Keywords
uncertainty quantification
(5)
out-of-distribution detection
(5)
semantic segmentation
(3)
epistemic uncertainty
(2)
uncertainty estimation
(2)
vision-language model
(2)
deep ensemble
(2)
aleatoric uncertainty
(2)
bayesian neural network
(2)
entropy minimization
(1)
object detection
(1)
domain adaptation
(1)
data augmentation
(1)
autonomous driving
(1)
adversarial robustness
(1)
bayesian inference
(1)
concept-based explanation
(1)
explainable ai
(1)
text-to-image generation
(1)
test-time adaptation
(1)
Papers
Benchmarking XAI Explanations with Human-Aligned Evaluations
AAAI 2026
Collaborative Instance Object Navigation: Leveraging Uncertainty-Awareness to Minimize Human-Agent Dialogues
ICCV 2025
Hierarchical Light Transformer Ensembles for Multimodal Trajectory Forecasting
WACV 2025
Towards Understanding and Quantifying Uncertainty for Text-to-Image Generation
CVPR 2025
Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It
ICLR 2025
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors
ICLR 2024
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression
AAAI 2024
Frustratingly Easy Test-Time Adaptation of Vision-Language Models
NeurIPS 2024
InfraParis: A Multi-Modal and Multi-Task Autonomous Driving Dataset
WACV 2024
Learning To Generate Training Datasets for Robust Semantic Segmentation
WACV 2024
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models
CVPR 2024
NECO: NEural Collapse Based Out-of-distribution detection
ICLR 2024
Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancement
ICLR 2024
Packed Ensembles for efficient uncertainty estimation
ICLR 2023
Latent Discriminant Deterministic Uncertainty
ECCV 2022
TRADI: Tracking Deep Neural network Weight Distributions
ECCV 2020