1 citations · 2 across the 13 of their papers we have counts for
16 papers
SERO: Semantic Prediction for Single-Step Object Removal
Amreen Hasheem Siraj, Alireza Javanmardi, Pragati Jaiswal +2
Object removal and semantic inpainting of missing regions remain inherently ill-posed, as multiple plausible completions may exist for a given scene. Recent diffusion-based methods…
Multi-View Face and Gesture Animation with Dynamic Gaussians
Alireza Javanmardi, Vippin Kumar Jeetmal, Christen Millerdurai +2
Creating photorealistic 3D human avatars with realistic upper-body motion remains challenging. Existing approaches either focus on the head and overlook hand gestures, or reconstru…
Uncertainty quantification via conformal prediction in data assimilation
Catherine George, Alireza Javanmardi, Tijana Janjić +1
Quantifying the evolution of uncertainty is critical to both probabilistic forecasting and data assimilation in numerical weather prediction. In this study, we investigate the appl…
Reliable Conformal Prediction for Ordinal Classification Using the Ranked Probability Score
Stefan Haas, Luca Killmaier, Alireza Javanmardi +1
Ordinal classification (OC) arises in high-stakes domains such as medicine and finance, where uncertainty quantification must account for the severity of ordinal errors. Conformal…
ReLaGS: Relational Language Gaussian Splatting
Yaxu Xie, Abdalla Arafa, Alireza Javanmardi +5
Achieving unified 3D perception and reasoning across tasks such as segmentation, retrieval, and relation understanding remains challenging, as existing methods are either object-ce…
TalkingPose: Efficient Face and Gesture Animation with Feedback-guided Diffusion Model
Alireza Javanmardi, Pragati Jaiswal, Tewodros Amberbir Habtegebrial +4
Recent advancements in diffusion models have significantly improved the realism and generalizability of character-driven animation, enabling the synthesis of high-quality motion fr…
Fine-Grained Uncertainty Decomposition in Large Language Models: A Spectral Approach
Nassim Walha, Sebastian G. Gruber, Thomas Decker +4
As Large Language Models (LLMs) are increasingly integrated in diverse applications, obtaining reliable measures of their predictive uncertainty has become critically important. A…
Optimal Conformal Prediction under Epistemic Uncertainty
Alireza Javanmardi, Soroush H. Zargarbashi, Santo M. A. R. Thies +3
Conformal prediction (CP) is a widely used frequentist framework to quantify uncertainty by constructing prediction sets with user-specified marginal coverage guarantees. In practi…
Masked Autoencoder Self Pre-Training for Defect Detection in Microelectronics
Nikolai Röhrich, Alwin Hoffmann, Richard Nordsieck +2
While transformers have surpassed convolutional neural networks (CNNs) in various computer vision tasks, microelectronics defect detection still largely relies on CNNs. We hypothes…
Conformal Prediction in Hierarchical Classification with Constrained Representation Complexity
Thomas Mortier, Alireza Javanmardi, Yusuf Sale +2
Conformal prediction has emerged as a widely used framework for constructing valid prediction sets in classification and regression tasks. In this work, we extend the split conform…
G3FA: Geometry-guided GAN for Face Animation
Alireza Javanmardi, Alain Pagani, Didier Stricker
Animating human face images aims to synthesize a desired source identity in a natural-looking way mimicking a driving video's facial movements. In this context, Generative Adversar…
Learning Images Across Scales Using Adversarial Training
Krzysztof Wolski, Adarsh Djeacoumar, Alireza Javanmardi +7
The real world exhibits rich structure and detail across many scales of observation. It is difficult, however, to capture and represent a broad spectrum of scales using ordinary im…
Conformalized Credal Set Predictors
Alireza Javanmardi, David Stutz, Eyke Hüllermeier
Credal sets are sets of probability distributions that are considered as candidates for an imprecisely known ground-truth distribution. In machine learning, they have recently attr…
Conformal Prediction with Partially Labeled Data
Alireza Javanmardi, Yusuf Sale, Paul Hofman +1
While the predictions produced by conformal prediction are set-valued, the data used for training and calibration is supposed to be precise. In the setting of superset learning or…
Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization
Navid Ansari, Alireza Javanmardi, Eyke Hüllermeier +2
Bayesian optimization (BO) provides a powerful framework for optimizing black-box, expensive-to-evaluate functions. It is therefore an attractive tool for engineering design proble…
Conformal Prediction Intervals for Remaining Useful Lifetime Estimation
Alireza Javanmardi, Eyke Hüllermeier
The main objective of Prognostics and Health Management is to estimate the Remaining Useful Lifetime (RUL), namely, the time that a system or a piece of equipment is still in worki…