MAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation
NeurIPS 2026
OSCAR: Orchestrated Self-verification and Cross-path Refinement
CoLM 2026
GE-FM: Geometry-aware Energy-based Flow Matching for Non Euclidean Manifolds
TMLR 2026
ManifoldGD: Training-Free Hierarchical Manifold Guidance for Diffusion-Based Dataset Distillation
CVPR 2026
Interpretable Prompts made Edit-Friendly: Token-to-Token Similarity Reduction in dLLMs for Edit-Friendly Hard Prompt Inversion
CVPR 2026
Is Exchangeability better than I.I.D to handle Data Distribution Shifts while Pooling Data for Data-scarce Medical image segmentation?
MIDL 2026
Beyond Pooling: Matching for Robust Generalization under Data Heterogeneity
AISTATS 2026
GeoTTER: Leveraging Local Geometry of Optimal Transport for Zero-Shot Classification
AISTATS 2026
Forget Less by Learning Together through Concept Consolidation
WACV 2026
Forget Less by Learning from Parents Through Hierarchical Relationships
AAAI 2026
Latent Diffusion Unlearning: Protecting against Unauthorized Personalization through Trajectory Shifted Perturbations
ACM Multimedia 2025
Your Text Encoder Can Be An Object-Level Watermarking Controller
ICCV 2025
Craft: Cross-modal Aligned Features Improve Robustness of Prompt Tuning
WACV 2025
ParallelEdits: Efficient Multi-Aspect Text-Driven Image Editing with Attention Grouping
NeurIPS 2024
Pooling Image Datasets with Multiple Covariate Shift and Imbalance
ICLR 2024
Efficient Discrete Multi Marginal Optimal Transport Regularization
ICLR 2023
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets
CVPR 2022
Towards Group Robustness in the presence of Partial Group Labels
ICML 2022
Pooling CSF Measurements Across Multiple Cohorts in the Preclinical Alzheimer's Consortium
AAIC 2022
Graph Reparameterizations for Enabling 1000+ Monte Carlo Iterations in Bayesian Deep Neural Networks
UAI 2021
Constrained Harmonization Algorithm for Pooling Multi-site Datasets
AAIC 2021
Learning Invariant Representations using Inverse Contrastive Loss
AAAI 2021
FairALM: An Augmented Lagrangian Method for Training Fair Models with Little Regret
ECCV 2020
Generating Accurate Pseudo-labels in Semi-Supervised Learning and Avoiding Overconfident Predictions via Hermite Polynomial Activations
CVPR 2020
Accelerating Column Generation via Flexible Dual Optimal Inequalities with Application to Entity Resolution
AAAI 2020
Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision
AAAI 2019