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Anees Kazi
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2020 – today
- 2024
- [j8]Tamara T. Mueller, Sophie Starck, Alina Dima, Stephan Wunderlich, Kyriaki-Margarita Bintsi, Kamilia Zaripova, Rickmer Braren, Daniel Rueckert, Anees Kazi, Georgios Kaissis:
A Survey on Graph Construction for Geometric Deep Learning in Medicine: Methods and Recommendations. Trans. Mach. Learn. Res. 2024 (2024) - [i21]Razieh Rezaei, Alireza Dizaji, Ashkan Khakzar, Anees Kazi, Nassir Navab, Daniel Rueckert:
On Discprecncies between Perturbation Evaluations of Graph Neural Network Attributions. CoRR abs/2401.00633 (2024) - [i20]Nairouz Shehata, Carolina Piçarra, Anees Kazi, Ben Glocker:
The Importance of Model Inspection for Better Understanding Performance Characteristics of Graph Neural Networks. CoRR abs/2405.01270 (2024) - 2023
- [j7]Kamilia Zaripova
, Luca Cosmo
, Anees Kazi, Seyed-Ahmad Ahmadi
, Michael M. Bronstein, Nassir Navab
:
Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications. Medical Image Anal. 88: 102839 (2023) - [j6]Chantal Pellegrini
, Nassir Navab
, Anees Kazi:
Unsupervised pre-training of graph transformers on patient population graphs. Medical Image Anal. 89: 102895 (2023) - [j5]Anees Kazi
, Luca Cosmo
, Seyed-Ahmad Ahmadi
, Nassir Navab
, Michael M. Bronstein:
Differentiable Graph Module (DGM) for Graph Convolutional Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1606-1617 (2023) - [c12]Haitz Sáez de Ocáriz Borde, Anees Kazi, Federico Barbero, Pietro Liò:
Latent Graph Inference using Product Manifolds. ICLR 2023 - [c11]Anees Kazi, Jocelyn S. Mora, Bruce Fischl, Adrian V. Dalca, Iman Aganj:
Multi-head Graph Convolutional Network for Structural Connectome Classification. GRAIL/OCELOT@MICCAI 2023: 27-36 - [c10]Anees Kazi, Soroush Farghadani, Iman Aganj, Nassir Navab:
IA-GCN: Interpretable Attention Based Graph Convolutional Network for Disease Prediction. MLMI@MICCAI (1) 2023: 382-392 - [i19]Anees Kazi, Jocelyn S. Mora, Bruce Fischl, Adrian V. Dalca, Iman Aganj:
Multi-Head Graph Convolutional Network for Structural Connectome Classification. CoRR abs/2305.02199 (2023) - 2022
- [j4]Mahsa Ghorbani, Anees Kazi, Mahdieh Soleymani Baghshah, Hamid R. Rabiee, Nassir Navab:
RA-GCN: Graph convolutional network for disease prediction problems with imbalanced data. Medical Image Anal. 75: 102272 (2022) - [c9]Anees Kazi, Viktoria Markova, Prabhat R. Kondamadugula, Beiyan Liu, Ahmed Adly, Shahrooz Faghihroohi, Nassir Navab:
DG-GRU: dynamic graph based gated recurrent unit for age and gender prediction using brain imaging. Medical Imaging: Computer-Aided Diagnosis 2022 - [e1]Luigi Manfredi
, Seyed-Ahmad Ahmadi
, Michael M. Bronstein, Anees Kazi, Davide Lomanto
, Alwyn Mathew, Ludovic Magerand
, Kamilia Mullakaeva, Bartlomiej W. Papiez
, Russell H. Taylor, Emanuele Trucco
:
Imaging Systems for GI Endoscopy, and Graphs in Biomedical Image Analysis - First MICCAI Workshop, ISGIE 2022, and Fourth MICCAI Workshop, GRAIL 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings. Lecture Notes in Computer Science 13754, Springer 2022, ISBN 978-3-031-21082-2 [contents] - [i18]Chantal Pellegrini, Anees Kazi, Nassir Navab:
Unsupervised Pre-Training on Patient Population Graphs for Patient-Level Predictions. CoRR abs/2203.12616 (2022) - [i17]Kamilia Mullakaeva, Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein:
Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications. CoRR abs/2204.00323 (2022) - [i16]Chantal Pellegrini, Nassir Navab, Anees Kazi:
Unsupervised pre-training of graph transformers on patient population graphs. CoRR abs/2207.10603 (2022) - [i15]Haitz Sáez de Ocáriz Borde, Anees Kazi, Federico Barbero, Pietro Liò:
Latent Graph Inference using Product Manifolds. CoRR abs/2211.16199 (2022) - 2021
- [j3]Gerome Vivar
, Anees Kazi, Hendrik Burwinkel, Andreas Zwergal, Nassir Navab, Seyed-Ahmad Ahmadi
:
Simultaneous imputation and classification using Multigraph Geometric Matrix Completion (MGMC): Application to neurodegenerative disease classification. Artif. Intell. Medicine 117: 102097 (2021) - [c8]Mahsa Ghorbani, Mojtaba Bahrami
, Anees Kazi, Mahdieh Soleymani Baghshah, Hamid R. Rabiee, Nassir Navab:
GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference. MICCAI (5) 2021: 709-718 - [i14]Mahsa Ghorbani, Anees Kazi, Mahdieh Soleymani Baghshah, Hamid R. Rabiee, Nassir Navab:
RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data. CoRR abs/2103.00221 (2021) - [i13]Anees Kazi, Soroush Farghadani, Nassir Navab:
IA-GCN: Interpretable Attention based Graph Convolutional Network for Disease prediction. CoRR abs/2103.15587 (2021) - [i12]Mahsa Ghorbani, Mojtaba Bahrami, Anees Kazi, Mahdieh Soleymani Baghshah, Hamid R. Rabiee, Nassir Navab:
GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference. CoRR abs/2104.03597 (2021) - 2020
- [j2]Amelia Jiménez-Sánchez
, Anees Kazi, Shadi Albarqouni
, Chlodwig Kirchhoff, Peter Biberthaler, Nassir Navab, Sonja Kirchhoff, Diana Mateus:
Precise proximal femur fracture classification for interactive training and surgical planning. Int. J. Comput. Assist. Radiol. Surg. 15(5): 847-857 (2020) - [c7]Luca Cosmo
, Anees Kazi, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein:
Latent-Graph Learning for Disease Prediction. MICCAI (2) 2020: 643-653 - [i11]Anees Kazi, Luca Cosmo, Nassir Navab, Michael M. Bronstein:
Differentiable Graph Module (DGM) Graph Convolutional Networks. CoRR abs/2002.04999 (2020) - [i10]Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein:
Latent Patient Network Learning for Automatic Diagnosis. CoRR abs/2003.13620 (2020) - [i9]Gerome Vivar, Anees Kazi, Hendrik Burwinkel, Andreas Zwergal, Nassir Navab, Seyed-Ahmad Ahmadi:
Simultaneous imputation and disease classification in incomplete medical datasets using Multigraph Geometric Matrix Completion (MGMC). CoRR abs/2005.06935 (2020)
2010 – 2019
- 2019
- [c6]Anees Kazi, Shayan Shekarforoush
, S. Arvind Krishna, Hendrik Burwinkel, Gerome Vivar, Karsten Kortüm, Seyed-Ahmad Ahmadi, Shadi Albarqouni
, Nassir Navab:
InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction. IPMI 2019: 73-85 - [c5]Anees Kazi, S. Arvind Krishna, Shayan Shekarforoush
, Karsten U. Kortuem, Shadi Albarqouni
, Nassir Navab:
Self-Attention Equipped Graph Convolutions for Disease Prediction. ISBI 2019: 1896-1899 - [c4]Anees Kazi, Shayan Shekarforoush
, S. Arvind Krishna, Hendrik Burwinkel, Gerome Vivar, Benedikt Wiestler
, Karsten Kortüm, Seyed-Ahmad Ahmadi, Shadi Albarqouni
, Nassir Navab:
Graph Convolution Based Attention Model for Personalized Disease Prediction. MICCAI (4) 2019: 122-130 - [c3]Hendrik Burwinkel, Anees Kazi, Gerome Vivar, Shadi Albarqouni
, Guillaume Zahnd, Nassir Navab, Seyed-Ahmad Ahmadi:
Adaptive Image-Feature Learning for Disease Classification Using Inductive Graph Networks. MICCAI (6) 2019: 640-648 - [i8]Amelia Jiménez-Sánchez
, Anees Kazi, Shadi Albarqouni, Chlodwig Kirchhoff, Peter Biberthaler, Nassir Navab, Diana Mateus, Sonja Kirchhoff:
Towards an Interactive and Interpretable CAD System to Support Proximal Femur Fracture Classification. CoRR abs/1902.01338 (2019) - [i7]Anees Kazi, Shayan Shekarforoush, S. Arvind Krishna, Hendrik Burwinkel, Gerome Vivar, Karsten U. Kortuem, Seyed-Ahmad Ahmadi, Shadi Albarqouni, Nassir Navab:
InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction. CoRR abs/1903.04233 (2019) - [i6]Hendrik Burwinkel, Anees Kazi, Gerome Vivar, Shadi Albarqouni, Guillaume Zahnd, Nassir Navab, Seyed-Ahmad Ahmadi:
Adaptive image-feature learning for disease classification using inductive graph networks. CoRR abs/1905.03036 (2019) - [i5]Gerome Vivar, Hendrik Burwinkel, Anees Kazi, Andreas Zwergal, Nassir Navab, Seyed-Ahmad Ahmadi:
Multi-modal Graph Fusion for Inductive Disease Classification in Incomplete Datasets. CoRR abs/1905.03053 (2019) - 2018
- [i4]Anees Kazi, Shadi Albarqouni, Karsten U. Kortuem, Nassir Navab:
Multi Layered-Parallel Graph Convolutional Network (ML-PGCN) for Disease Prediction. CoRR abs/1804.10776 (2018) - [i3]Amelia Jiménez-Sánchez, Anees Kazi, Shadi Albarqouni, Sonja Kirchhoff, Alexandra Sträter, Peter Biberthaler, Diana Mateus, Nassir Navab:
Weakly-Supervised Localization and Classification of Proximal Femur Fractures. CoRR abs/1809.10692 (2018) - [i2]Anees Kazi, S. Arvind Krishna, Shayan Shekarforoush, Karsten U. Kortuem, Shadi Albarqouni, Nassir Navab:
Self-Attention Equipped Graph Convolutions for Disease Prediction. CoRR abs/1812.09954 (2018) - 2017
- [c2]Anees Kazi, Sailesh Conjeti, Amin Katouzian, Nassir Navab:
Coupled Manifold Learning for Retrieval Across Modalities. ICCV Workshops 2017: 1321-1328 - [c1]Anees Kazi, Shadi Albarqouni
, Amelia Jiménez-Sánchez, Sonja Kirchhoff, Peter Biberthaler, Nassir Navab, Diana Mateus
:
Automatic Classification of Proximal Femur Fractures Based on Attention Models. MLMI@MICCAI 2017: 70-78 - 2016
- [j1]Sailesh Conjeti, Amin Katouzian, Anees Kazi, Sepideh Mesbah, David Beymer, Tanveer F. Syeda-Mahmood, Nassir Navab:
Metric hashing forests. Medical Image Anal. 34: 13-29 (2016) - [i1]Sailesh Conjeti, Anees Kazi, Nassir Navab, Amin Katouzian:
Cross-Modal Manifold Learning for Cross-modal Retrieval. CoRR abs/1612.06098 (2016)
Coauthor Index
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last updated on 2024-08-10 01:26 CEST by the dblp team
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