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ORCIDMichael Kampffmeyer
Michael C. Kampffmeyer – Michael Christian Kampffmeyer
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2020 – today
- 2024
[j32]Nanqing Dong
, Michael Kampffmeyer, Haoyang Su, Eric P. Xing:
An exploratory study of self-supervised pre-training on partially supervised multi-label classification on chest X-ray images. Appl. Soft Comput. 163: 111855 (2024)- [j31]Duy Khoi Tran, Van Nhan Nguyen, Davide Roverso, Robert Jenssen, Michael Kampffmeyer:
LSNetv2: Improving weakly supervised power line detection with bipartite matching. Expert Syst. Appl. 250: 123773 (2024) - [j30]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Discriminative multimodal learning via conditional priors in generative models. Neural Networks 169: 417-430 (2024) - [j29]Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael Kampffmeyer:
Leveraging tensor kernels to reduce objective function mismatch in deep clustering. Pattern Recognit. 149: 110229 (2024) - [j28]Nanqing Dong, Zhipeng Wang, Jiahao Sun, Michael Kampffmeyer, William J. Knottenbelt, Eric P. Xing:
Defending Against Poisoning Attacks in Federated Learning With Blockchain. IEEE Trans. Artif. Intell. 5(7): 3743-3756 (2024) - [j27]Srishti Gautam, Ahcene Boubekki, Marina M.-C. Höhne, Michael Kampffmeyer:
Prototypical Self-Explainable Models Without Re-training. Trans. Mach. Learn. Res. 2024 (2024) - [j26]Luigi Tommaso Luppino, Mads A. Hansen, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Robert Jenssen, Stian Normann Anfinsen:
Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images. IEEE Trans. Neural Networks Learn. Syst. 35(1): 60-72 (2024) - [c46]Luoyang Lin, Zutao Jiang, Xiaodan Liang, Liqian Ma, Michael C. Kampffmeyer, Xiaochun Cao:
PTUS: Photo-Realistic Talking Upper-Body Synthesis via 3D-Aware Motion Decomposition Warping. AAAI 2024: 3441-3449 - [c45]Changkyu Choi, Shujian Yu, Michael Kampffmeyer, Arnt-Børre Salberg, Nils Olav Handegard, Robert Jenssen:
DIB-X: Formulating Explainability Principles for a Self-Explainable Model Through Information Theoretic Learning. ICASSP 2024: 7170-7174 - [i67]Rwiddhi Chakraborty, Adrian Sletten, Michael Kampffmeyer:
ExMap: Leveraging Explainability Heatmaps for Unsupervised Group Robustness to Spurious Correlations. CoRR abs/2403.13870 (2024) - [i66]Xujie Zhang, Ente Lin, Xiu Li, Yuxuan Luo, Michael Kampffmeyer, Xin Dong, Xiaodan Liang:
MMTryon: Multi-Modal Multi-Reference Control for High-Quality Fashion Generation. CoRR abs/2405.00448 (2024) - [i65]Markus Heinonen, Ba-Hien Tran, Michael Kampffmeyer, Maurizio Filippone:
Robust Classification by Coupling Data Mollification with Label Smoothing. CoRR abs/2406.01494 (2024) - 2023
- [j25]Kristoffer Knutsen Wickstrøm, Eirik Agnalt Østmo, Keyur Radiya, Karl Øyvind Mikalsen, Michael Christian Kampffmeyer, Robert Jenssen:
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images. Comput. Medical Imaging Graph. 107: 102239 (2023) - [j24]Kristoffer K. Wickstrøm, Sigurd Løkse, Michael C. Kampffmeyer, Shujian Yu, José C. Príncipe, Robert Jenssen:
Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy. Entropy 25(6): 899 (2023) - [j23]Kristoffer K. Wickstrøm, Daniel J. Trosten, Sigurd Løkse, Ahcène Boubekki, Karl Øyvind Mikalsen, Michael C. Kampffmeyer, Robert Jenssen:
RELAX: Representation Learning Explainability. Int. J. Comput. Vis. 131(6): 1584-1610 (2023) - [j22]Stine Hansen, Srishti Gautam, Suaiba Amina Salahuddin, Michael Kampffmeyer, Robert Jenssen:
ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement. Medical Image Anal. 89: 102870 (2023) - [j21]Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer:
This looks More Like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation. Pattern Recognit. 136: 109172 (2023) - [j20]Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing:
Federated Partially Supervised Learning With Limited Decentralized Medical Images. IEEE Trans. Medical Imaging 42(7): 1944-1954 (2023) - [c44]Daniel J. Trosten, Rwiddhi Chakraborty, Sigurd Løkse, Kristoffer Knutsen Wickstrøm, Robert Jenssen, Michael C. Kampffmeyer:
Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-Shot Learning with Hyperspherical Embeddings. CVPR 2023: 7527-7536 - [c43]Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael C. Kampffmeyer:
On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering. CVPR 2023: 23976-23985 - [c42]Durgesh Singh, Ahcène Boubekki, Robert Jenssen, Michael C. Kampffmeyer:
Supercm: Revisiting Clustering for Semi-Supervised Learning. ICASSP 2023: 1-5 - [c41]Haoyuan Li, Haoye Dong, Hanchao Jia, Dong Huang, Michael C. Kampffmeyer, Liang Lin, Xiaodan Liang:
Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos. ICCV 2023: 8710-8719 - [c40]Xujie Zhang, Binbin Yang, Michael C. Kampffmeyer, Wenqing Zhang, Shiyue Zhang, Guansong Lu, Liang Lin, Hang Xu, Xiaodan Liang:
DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment. ICCV 2023: 23097-23106 - [c39]Luca Tomasetti, Stine Hansen, Mahdieh Khanmohammadi, Kjersti Engan, Liv Jorunn Høllesli, Kathinka Dæhli Kurz, Michael Kampffmeyer:
Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation. ISBI 2023: 1-5 - [c38]Eirik Agnalt Østmo, Kristoffer K. Wickstrøm, Keyur Radiya, Michael C. Kampffmeyer, Robert Jenssen:
View it Like a Radiologist: Shifted Windows for Deep Learning Augmentation Of CT Images. MLSP 2023: 1-6 - [i64]Luca Tomasetti, Stine Hansen, Mahdieh Khanmohammadi, Kjersti Engan, Liv Jorunn Høllesli, Kathinka Dæhli Kurz, Michael Kampffmeyer:
Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation. CoRR abs/2303.01332 (2023) - [i63]Daniel J. Trosten, Rwiddhi Chakraborty, Sigurd Løkse, Kristoffer Knutsen Wickstrøm, Robert Jenssen, Michael C. Kampffmeyer:
Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings. CoRR abs/2303.09352 (2023) - [i62]Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael C. Kampffmeyer:
On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering. CoRR abs/2303.09877 (2023) - [i61]Sara Björk, Stian Normann Anfinsen, Michael Kampffmeyer, Erik Næsset, Terje Gobakken, Lennart Noordermeer:
Forest Parameter Prediction by Multiobjective Deep Learning of Regression Models Trained with Pseudo-Target Imputation. CoRR abs/2306.11103 (2023) - [i60]Nanqing Dong, Zhipeng Wang, Jiahao Sun, Michael Kampffmeyer, Yizhe Wen, Shuoying Zhang, William J. Knottenbelt, Eric P. Xing:
Defending Against Malicious Behaviors in Federated Learning with Blockchain. CoRR abs/2307.00543 (2023) - [i59]Haoyuan Li, Haoye Dong, Hanchao Jia, Dong Huang, Michael C. Kampffmeyer, Liang Lin, Xiaodan Liang:
Coordinate Transformer: Achieving Single-stage Multi-person Mesh Recovery from Videos. CoRR abs/2308.10334 (2023) - [i58]Xujie Zhang, Binbin Yang, Michael C. Kampffmeyer, Wenqing Zhang, Shiyue Zhang, Guansong Lu, Liang Lin, Hang Xu, Xiaodan Liang:
DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment. CoRR abs/2308.11206 (2023) - [i57]Eirik Agnalt Østmo, Kristoffer K. Wickstrøm, Keyur Radiya, Michael C. Kampffmeyer, Robert Jenssen:
View it like a radiologist: Shifted windows for deep learning augmentation of CT images. CoRR abs/2311.14990 (2023) - [i56]Xujie Zhang, Xiu Li, Michael Kampffmeyer, Xin Dong, Zhenyu Xie, Feida Zhu, Haoye Dong, Xiaodan Liang:
WarpDiffusion: Efficient Diffusion Model for High-Fidelity Virtual Try-on. CoRR abs/2312.03667 (2023) - [i55]Ribana Roscher, Marc Rußwurm, Caroline Gevaert, Michael Kampffmeyer, Jefersson A. dos Santos, Maria Vakalopoulou, Ronny Hänsch, Stine Hansen, Keiller Nogueira, Jonathan Prexl, Devis Tuia:
Data-Centric Machine Learning for Geospatial Remote Sensing Data. CoRR abs/2312.05327 (2023) - [i54]Srishti Gautam, Ahcene Boubekki, Marina M.-C. Höhne, Michael C. Kampffmeyer:
Prototypical Self-Explainable Models Without Re-training. CoRR abs/2312.07822 (2023) - 2022
- [j19]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Min Xu, Irina Voiculescu, Eric P. Xing:
Towards robust partially supervised multi-structure medical image segmentation on small-scale data. Appl. Soft Comput. 114: 108074 (2022) - [j18]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Generating customer's credit behavior with deep generative models. Knowl. Based Syst. 245: 108568 (2022) - [j17]Stine Hansen, Srishti Gautam, Robert Jenssen, Michael Kampffmeyer:
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels. Medical Image Anal. 78: 102385 (2022) - [j16]Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing:
Negational symmetry of quantum neural networks for binary pattern classification. Pattern Recognit. 129: 108750 (2022) - [j15]Kristoffer Wickstrøm, Michael Kampffmeyer, Karl Øyvind Mikalsen, Robert Jenssen:
Mixing up contrastive learning: Self-supervised representation learning for time series. Pattern Recognit. Lett. 155: 54-61 (2022) - [j14]Luigi Tommaso Luppino, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Sebastiano Bruno Serpico, Robert Jenssen, Stian Normann Anfinsen:
Deep Image Translation With an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection. IEEE Trans. Geosci. Remote. Sens. 60: 1-22 (2022) - [c37]Suaiba Amina Salahuddin, Stine Hansen, Srishti Gautam, Michael Kampffmeyer, Robert Jenssen:
A self-guided anomaly detection-inspired few-shot segmentation network. CVCS 2022 - [c36]Xiao Dong, Xunlin Zhan, Yangxin Wu, Yunchao Wei, Michael C. Kampffmeyer, Xiaoyong Wei, Minlong Lu, Yaowei Wang, Xiaodan Liang:
M5Product: Self-harmonized Contrastive Learning for E-commercial Multi-modal Pretraining. CVPR 2022: 21220-21230 - [c35]Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer:
Demonstrating the Risk of Imbalanced Datasets in Chest X-Ray Image-Based Diagnostics by Prototypical Relevance Propagation. ISBI 2022: 1-5 - [c34]Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu:
Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images. MICCAI (8) 2022: 67-76 - [c33]Xujie Zhang, Yu Sha, Michael C. Kampffmeyer, Zhenyu Xie, Zequn Jie, Chengwen Huang, Jianqing Peng, Xiaodan Liang:
ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design. ACM Multimedia 2022: 4525-4535 - [c32]Kristoffer Wickstrøm, Juan Emmanuel Johnson, Sigurd Løkse, Gustau Camps-Valls, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen:
The Kernelized Taylor Diagram. NAIS 2022: 125-131 - [c31]Srishti Gautam, Ahcène Boubekki, Stine Hansen, Suaiba Amina Salahuddin, Robert Jenssen, Marina M.-C. Höhne, Michael Kampffmeyer:
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model. NeurIPS 2022 - [c30]Zaiyu Huang, Hanhui Li, Zhenyu Xie, Michael Kampffmeyer, Qingling Cai, Xiaodan Liang:
Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning. NeurIPS 2022 - [i53]Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer:
Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation. CoRR abs/2201.03559 (2022) - [i52]Stine Hansen, Srishti Gautam, Robert Jenssen, Michael Kampffmeyer:
Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels. CoRR abs/2203.02048 (2022) - [i51]Kristoffer Wickstrøm, Michael Kampffmeyer, Karl Øyvind Mikalsen, Robert Jenssen:
Mixing Up Contrastive Learning: Self-Supervised Representation Learning for Time Series. CoRR abs/2203.09270 (2022) - [i50]Jonas Lederer, Michael Gastegger, Kristof T. Schütt, Michael Kampffmeyer, Klaus-Robert Müller, Oliver T. Unke:
Automatic Identification of Chemical Moieties. CoRR abs/2203.16205 (2022) - [i49]Kristoffer Wickstrøm, Juan Emmanuel Johnson, Sigurd Løkse, Gustau Camps-Valls, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen:
The Kernelized Taylor Diagram. CoRR abs/2205.08864 (2022) - [i48]Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu:
Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images. CoRR abs/2206.15353 (2022) - [i47]Kristoffer Knutsen Wickstrøm, Eirik Agnalt Østmo, Keyur Radiya, Karl Øyvind Mikalsen, Michael Christian Kampffmeyer, Robert Jenssen:
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images. CoRR abs/2207.04812 (2022) - [i46]Zhenyu Xie, Zaiyu Huang, Fuwei Zhao, Haoye Dong, Michael Kampffmeyer, Xin Dong, Feida Zhu, Xiaodan Liang:
PASTA-GAN++: A Versatile Framework for High-Resolution Unpaired Virtual Try-on. CoRR abs/2207.13475 (2022) - [i45]Xujie Zhang, Yu Sha, Michael C. Kampffmeyer, Zhenyu Xie, Zequn Jie, Chengwen Huang, Jianqing Peng, Xiaodan Liang:
ARMANI: Part-level Garment-Text Alignment for Unified Cross-Modal Fashion Design. CoRR abs/2208.05621 (2022) - [i44]Srishti Gautam, Ahcene Boubekki, Stine Hansen, Suaiba Amina Salahuddin, Robert Jenssen, Marina M.-C. Höhne, Michael Kampffmeyer:
ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model. CoRR abs/2210.08151 (2022) - [i43]Zaiyu Huang, Hanhui Li, Zhenyu Xie, Michael Kampffmeyer, Qingling Cai, Xiaodan Liang:
Towards Hard-pose Virtual Try-on via 3D-aware Global Correspondence Learning. CoRR abs/2211.14052 (2022) - 2021
- [j13]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Learning latent representations of bank customers with the Variational Autoencoder. Expert Syst. Appl. 164: 114020 (2021) - [j12]Stine Hansen, Samuel Kuttner, Michael Kampffmeyer, Tom-Vegard Markussen, Rune Sundset, Silje Kjærnes Øen, Live Eikenes, Robert Jenssen:
Unsupervised supervoxel-based lung tumor segmentation across patient scans in hybrid PET/MRI. Expert Syst. Appl. 167: 114244 (2021) - [j11]Ahcène Boubekki, Michael Kampffmeyer, Ulf Brefeld, Robert Jenssen:
Joint optimization of an autoencoder for clustering and embedding. Mach. Learn. 110(7): 1901-1937 (2021) - [j10]Kristoffer Wickstrøm, Karl Øyvind Mikalsen, Michael Kampffmeyer, Arthur Revhaug, Robert Jenssen:
Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series. IEEE J. Biomed. Health Informatics 25(7): 2435-2444 (2021) - [c29]Nanqing Dong, Michael C. Kampffmeyer, Irina Voiculescu:
Quantum Unsupervised Domain Adaptation: Does Entanglement Help? BMVC 2021: 287 - [c28]Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael Kampffmeyer:
Reconsidering Representation Alignment for Multi-View Clustering. CVPR 2021: 1255-1265 - [c27]Fuwei Zhao, Zhenyu Xie, Michael Kampffmeyer, Haoye Dong, Songfang Han, Tianxiang Zheng, Tao Zhang, Xiaodan Liang:
M3D-VTON: A Monocular-to-3D Virtual Try-On Network. ICCV 2021: 13219-13229 - [c26]Zhenyu Xie, Xujie Zhang, Fuwei Zhao, Haoye Dong, Michael C. Kampffmeyer, Haonan Yan, Xiaodan Liang:
WAS-VTON: Warping Architecture Search for Virtual Try-on Network. ACM Multimedia 2021: 3350-3359 - [c25]Zhenyu Xie, Zaiyu Huang, Fuwei Zhao, Haoye Dong, Michael Kampffmeyer, Xiaodan Liang:
Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN. NeurIPS 2021: 2598-2610 - [c24]Daniel J. Trosten, Robert Jenssen, Michael C. Kampffmeyer:
Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective. NLDL 2021 - [c23]Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu:
Self-supervised Multi-task Representation Learning for Sequential Medical Images. ECML/PKDD (3) 2021: 779-794 - [i42]Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael Kampffmeyer:
Reconsidering Representation Alignment for Multi-view Clustering. CoRR abs/2103.07738 (2021) - [i41]Nanqing Dong, Michael Kampffmeyer, Irina Voiculescu, Eric P. Xing:
Negational Symmetry of Quantum Neural Networks for Binary Pattern Classification. CoRR abs/2105.09580 (2021) - [i40]Zhenyu Xie, Xujie Zhang, Fuwei Zhao, Haoye Dong, Michael C. Kampffmeyer, Haonan Yan, Xiaodan Liang:
WAS-VTON: Warping Architecture Search for Virtual Try-on Network. CoRR abs/2108.00386 (2021) - [i39]Fuwei Zhao, Zhenyu Xie, Michael Kampffmeyer, Haoye Dong, Songfang Han, Tianxiang Zheng, Tao Zhang, Xiaodan Liang:
M3D-VTON: A Monocular-to-3D Virtual Try-On Network. CoRR abs/2108.05126 (2021) - [i38]Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer:
This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation. CoRR abs/2108.12204 (2021) - [i37]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Discriminative Multimodal Learning via Conditional Priors in Generative Models. CoRR abs/2110.04616 (2021) - [i36]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
Multi-modal land cover mapping of remote sensing images using pyramid attention and gated fusion networks. CoRR abs/2111.03845 (2021) - [i35]Zhenyu Xie, Zaiyu Huang, Fuwei Zhao, Haoye Dong, Michael Kampffmeyer, Xiaodan Liang:
Towards Scalable Unpaired Virtual Try-On via Patch-Routed Spatially-Adaptive GAN. CoRR abs/2111.10544 (2021) - [i34]Kristoffer K. Wickstrøm, Daniel J. Trosten, Sigurd Løkse, Karl Øyvind Mikalsen, Michael C. Kampffmeyer, Robert Jenssen:
RELAX: Representation Learning Explainability. CoRR abs/2112.10161 (2021) - 2020
- [j9]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Deep generative models for reject inference in credit scoring. Knowl. Based Syst. 196: 105758 (2020) - [j8]Kristoffer Wickstrøm, Michael Kampffmeyer, Robert Jenssen:
Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps. Medical Image Anal. 60 (2020) - [j7]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
Dense Dilated Convolutions' Merging Network for Land Cover Classification. IEEE Trans. Geosci. Remote. Sens. 58(9): 6309-6320 (2020) - [c22]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
Multi-view Self-Constructing Graph Convolutional Networks with Adaptive Class Weighting Loss for Semantic Segmentation. CVPR Workshops 2020: 199-205 - [c21]Mang Tik Chiu, Xingqian Xu, Kai Wang, Jennifer A. Hobbs, Naira Hovakimyan, Thomas S. Huang, Honghui Shi, Yunchao Wei, Zilong Huang, Alexander G. Schwing, Robert Brunner, Ivan Dozier, Wyatt Dozier, Karen Ghandilyan, David Wilson, Hyunseong Park, Jun Hee Kim, Sungho Kim, Qinghui Liu, Michael C. Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg, Alexandre Barbosa, Rodrigo G. Trevisan, Bingchen Zhao, Shaozuo Yu, Siwei Yang, Yin Wang, Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng, Van Thong Huynh, Soo-Hyung Kim, In Seop Na, Ujjwal Baid, Shubham Innani, Prasad Dutande, Bhakti Baheti, Sanjay N. Talbar, Jianyu Tang:
The 1st Agriculture-Vision Challenge: Methods and Results. CVPR Workshops 2020: 212-218 - [c20]Van Nhan Nguyen, Sigurd Løkse, Kristoffer Wickstrøm, Michael Kampffmeyer, Davide Roverso, Robert Jenssen:
SEN: A Novel Feature Normalization Dissimilarity Measure for Prototypical Few-Shot Learning Networks. ECCV (23) 2020: 118-134 - [c19]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
Self-Constructing Graph Convolutional Networks for Semantic Labeling. IGARSS 2020: 1801-1804 - [i33]Luigi Tommaso Luppino, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Sebastiano Bruno Serpico, Robert Jenssen, Stian Normann Anfinsen:
Deep Image Translation with an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection. CoRR abs/2001.04271 (2020) - [i32]Daniel J. Trosten, Michael C. Kampffmeyer, Robert Jenssen:
Deep Image Clustering with Tensor Kernels and Unsupervised Companion Objectives. CoRR abs/2001.07026 (2020) - [i31]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
Dense Dilated Convolutions Merging Network for Land Cover Classification. CoRR abs/2003.04027 (2020) - [i30]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
Self-Constructing Graph Convolutional Networks for Semantic Labeling. CoRR abs/2003.06932 (2020) - [i29]Luigi Tommaso Luppino, Mads A. Hansen, Michael Kampffmeyer, Filippo Maria Bianchi, Gabriele Moser, Robert Jenssen, Stian Normann Anfinsen:
Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images. CoRR abs/2004.07011 (2020) - [i28]Mang Tik Chiu, Xingqian Xu, Kai Wang, Jennifer A. Hobbs, Naira Hovakimyan, Thomas S. Huang, Honghui Shi, Yunchao Wei, Zilong Huang, Alexander G. Schwing, Robert Brunner, Ivan Dozier, Wyatt Dozier, Karen Ghandilyan, David Wilson, Hyunseong Park, Jun Hee Kim, Sungho Kim, Qinghui Liu, Michael C. Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg, Alexandre Barbosa, Rodrigo G. Trevisan, Bingchen Zhao, Shaozuo Yu, Siwei Yang, Yin Wang, Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Y. Ng, Van Thong Huynh, Soo-Hyung Kim, In Seop Na, Ujjwal Baid, Shubham Innani, Prasad Dutande, Bhakti Baheti, Sanjay N. Talbar, Jianyu Tang:
The 1st Agriculture-Vision Challenge: Methods and Results. CoRR abs/2004.09754 (2020) - [i27]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
Multi-view Self-Constructing Graph Convolutional Networks with Adaptive Class Weighting Loss for Semantic Segmentation. CoRR abs/2004.10327 (2020) - [i26]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation. CoRR abs/2009.01599 (2020) - [i25]Kristoffer Wickstrøm, Karl Øyvind Mikalsen, Michael Kampffmeyer, Arthur Revhaug, Robert Jenssen:
Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series. CoRR abs/2010.11310 (2020) - [i24]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Min Xu, Irina Voiculescu, Eric P. Xing:
Towards Robust Medical Image Segmentation on Small-Scale Data with Incomplete Labels. CoRR abs/2011.14164 (2020) - [i23]Ahcène Boubekki, Michael Kampffmeyer, Ulf Brefeld, Robert Jenssen:
Joint Optimization of an Autoencoder for Clustering and Embedding. CoRR abs/2012.03740 (2020)
2010 – 2019
- 2019
- [j6]Yujia Zhang, Michael Kampffmeyer, Xiaodan Liang, Dingwen Zhang, Min Tan, Eric P. Xing:
Dilated temporal relational adversarial network for generic video summarization. Multim. Tools Appl. 78(24): 35237-35261 (2019) - [j5]Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Lorenzo Livi, Arnt-Børre Salberg, Robert Jenssen:
Deep divergence-based approach to clustering. Neural Networks 113: 91-101 (2019) - [j4]Filippo Maria Bianchi, Lorenzo Livi, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen:
Learning representations of multivariate time series with missing data. Pattern Recognit. 96 (2019) - [j3]Michael Kampffmeyer, Nanqing Dong, Xiaodan Liang, Yujia Zhang, Eric P. Xing:
ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation. IEEE Trans. Image Process. 28(5): 2518-2529 (2019) - [c18]Yujia Zhang, Michael Kampffmeyer, Xiaoguang Zhao, Min Tan:
DTR-GAN: dilated temporal relational adversarial network for video summarization. ACM TUR-C 2019: 89:1-89:6 - [c17]Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang, Hao Wang, Yujia Zhang, Eric P. Xing:
Rethinking Knowledge Graph Propagation for Zero-Shot Learning. CVPR 2019: 11487-11496 - [c16]Daniel J. Trosten, Andreas Storvik Strauman, Michael Kampffmeyer, Robert Jenssen:
Recurrent Deep Divergence-based Clustering for Simultaneous Feature Learning and Clustering of Variable Length Time Series. ICASSP 2019: 3257-3261 - [c15]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
Road Mapping in Lidar Images Using a Joint-Task Dense Dilated Convolutions Merging Network. IGARSS 2019: 5041-5044 - [c14]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images. JURSE 2019: 1-4 - [i22]Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Lorenzo Livi, Arnt-Børre Salberg, Robert Jenssen:
Deep Divergence-Based Approach to Clustering. CoRR abs/1902.04981 (2019) - [i21]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Learning Latent Representations of Bank Customers With The Variational Autoencoder. CoRR abs/1903.06580 (2019) - [i20]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images. CoRR abs/1908.11799 (2019) - [i19]Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg:
Road Mapping In LiDAR Images Using A Joint-Task Dense Dilated Convolutions Merging Network. CoRR abs/1909.04588 (2019) - [i18]Kristoffer Wickstrøm, Sigurd Løkse, Michael Kampffmeyer, Shujian Yu, José C. Príncipe, Robert Jenssen:
Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels. CoRR abs/1909.11396 (2019) - 2018
- [j2]Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi:
The deep kernelized autoencoder. Appl. Soft Comput. 71: 816-825 (2018) - [j1]Michael Kampffmeyer, Arnt-Børre Salberg, Robert Jenssen:
Urban Land Cover Classification With Missing Data Modalities Using Deep Convolutional Neural Networks. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 11(6): 1758-1768 (2018) - [c13]Andreas Storvik Strauman, Filippo Maria Bianchi, Karl Øyvind Mikalsen, Michael Kampffmeyer, Cristina Soguero-Ruíz, Robert Jenssen:
Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks. BHI 2018: 307-310 - [c12]Mads A. Hansen, Karl Øyvind Mikalsen, Michael Kampffmeyer, Cristina Soguero-Ruíz, Robert Jenssen:
Towards deep anchor learning. BHI 2018: 315-318 - [c11]Yujia Zhang, Michael Kampffmeyer, Xiaodan Liang, Min Tan, Eric P. Xing:
Query-Conditioned Three-Player Adversarial Network for Video Summarization. BMVC 2018: 288 - [c10]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing:
Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-Slide Images. DLMIA/ML-CDS@MICCAI 2018: 317-325 - [c9]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing:
Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio. MICCAI (2) 2018: 544-552 - [c8]Kristoffer Wickstrøm, Michael Kampffmeyer, Robert Jenssen:
Uncertainty Modeling and interpretability in Convolutional Neural Networks for Polyp Segmentation. MLSP 2018: 1-6 - [i17]Michael Kampffmeyer, Nanqing Dong, Xiaodan Liang, Yujia Zhang, Eric P. Xing:
ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation. CoRR abs/1804.07836 (2018) - [i16]Yujia Zhang, Michael Kampffmeyer, Xiaodan Liang, Dingwen Zhang, Min Tan, Eric P. Xing:
DTR-GAN: Dilated Temporal Relational Adversarial Network for Video Summarization. CoRR abs/1804.11228 (2018) - [i15]Filippo Maria Bianchi, Lorenzo Livi, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen:
Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders. CoRR abs/1805.03473 (2018) - [i14]Michael Kampffmeyer, Yinbo Chen, Xiaodan Liang, Hao Wang, Yujia Zhang, Eric P. Xing:
Rethinking Knowledge Graph Propagation for Zero-Shot Learning. CoRR abs/1805.11724 (2018) - [i13]Rogelio Andrade Mancisidor, Michael Kampffmeyer, Kjersti Aas, Robert Jenssen:
Segment-Based Credit Scoring Using Latent Clusters in the Variational Autoencoder. CoRR abs/1806.02538 (2018) - [i12]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing:
Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio. CoRR abs/1807.03434 (2018) - [i11]Rajesh Chidambaram, Michael Kampffmeyer, Willie Neiswanger, Xiaodan Liang, Thomas Lachmann, Eric P. Xing:
Geometric Generalization Based Zero-Shot Learning Dataset Infinite World: Simple Yet Powerful. CoRR abs/1807.03711 (2018) - [i10]Yujia Zhang, Michael Kampffmeyer, Xiaodan Liang, Min Tan, Eric P. Xing:
Query-Conditioned Three-Player Adversarial Network for Video Summarization. CoRR abs/1807.06677 (2018) - [i9]Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi:
The Deep Kernelized Autoencoder. CoRR abs/1807.07868 (2018) - [i8]Kristoffer Wickstrøm, Michael Kampffmeyer, Robert Jenssen:
Uncertainty and Interpretability in Convolutional Neural Networks for Semantic Segmentation of Colorectal Polyps. CoRR abs/1807.10584 (2018) - [i7]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing:
Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-slide Images. CoRR abs/1807.11113 (2018) - [i6]Daniel J. Trosten, Andreas Storvik Strauman, Michael Kampffmeyer, Robert Jenssen:
Recurrent Deep Divergence-based Clustering for simultaneous feature learning and clustering of variable length time series. CoRR abs/1811.12050 (2018) - 2017
- [b1]Filippo Maria Bianchi, Enrico Maiorino, Michael C. Kampffmeyer, Antonello Rizzi, Robert Jenssen:
Recurrent Neural Networks for Short-Term Load Forecasting - An Overview and Comparative Analysis. Springer Briefs in Computer Science, Springer 2017, ISBN 978-3-319-70337-4, pp. 1-72 - [c7]Jonas Nordhaug Myhre, Michael Kampffmeyer, Robert Jenssen:
Density ridge manifold traversal. ICASSP 2017: 2342-2346 - [c6]Michael Kampffmeyer, Arnt-Børre Salberg, Robert Jenssen:
Urban land cover classification with missing data using deep convolutional neural networks. IGARSS 2017: 5161-5164 - [c5]Filippo Maria Bianchi, Michael Kampffmeyer, Enrico Maiorino, Robert Jenssen:
Temporal overdrive recurrent neural network. IJCNN 2017: 4275-4282 - [c4]Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Lorenzo Livi, Arnt-Børre Salberg, Robert Jenssen:
Deep divergence-based clustering. MLSP 2017: 1-6 - [c3]Arnt-Børre Salberg, Øivind Due Trier, Michael Kampffmeyer:
Large-Scale Mapping of Small Roads in Lidar Images Using Deep Convolutional Neural Networks. SCIA (2) 2017: 193-204 - [c2]Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi:
Deep Kernelized Autoencoders. SCIA (1) 2017: 419-430 - [i5]Filippo Maria Bianchi, Michael Kampffmeyer, Enrico Maiorino, Robert Jenssen:
Temporal Overdrive Recurrent Neural Network. CoRR abs/1701.05159 (2017) - [i4]Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi:
Deep Kernelized Autoencoders. CoRR abs/1702.02526 (2017) - [i3]Filippo Maria Bianchi, Enrico Maiorino, Michael C. Kampffmeyer, Antonello Rizzi, Robert Jenssen:
An overview and comparative analysis of Recurrent Neural Networks for Short Term Load Forecasting. CoRR abs/1705.04378 (2017) - [i2]Michael Kampffmeyer, Arnt-Børre Salberg, Robert Jenssen:
Urban Land Cover Classification with Missing Data Using Deep Convolutional Neural Networks. CoRR abs/1709.07383 (2017) - [i1]Andreas Storvik Strauman, Filippo Maria Bianchi, Karl Øyvind Mikalsen, Michael Kampffmeyer, Cristina Soguero-Ruíz, Robert Jenssen:
Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks. CoRR abs/1711.06516 (2017) - 2016
- [c1]Michael Kampffmeyer, Arnt-Børre Salberg, Robert Jenssen:
Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks. CVPR Workshops 2016: 680-688
Coauthor Index
[j31] [j30] [j29] [j26] [c45] [j25] [j24] [j23] [j22] [j21] [c44] [c43] [c42] [c38] [i63] [i62] [i57] [j18] [j17] [j15] [j14] [c37] [c35] [c32] [c31] [i53] [i52] [i51] [i49] [i47] [i44] [j13] [j12] [j11] [j10] [c28] [c24] [i42] [i38] [i37] [i36] [i34] [j9] [j8] [j7] [c22] [c21] [c20] [c19] [i33] [i32] [i31] [i30] [i29] [i28] [i27] [i26] [i25] [i23] [j5] [j4] [c16] [c15] [c14] [i22] [i21] [i20] [i19] [i18] [j2] [j1] [c13] [c12] [c8] [i15] [i13] [i9] [i8] [i6] [b1] [c7] [c6] [c5] [c4] [c2] [i5] [i4] [i3] [i2] [i1] [c1]
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