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ORCIDSadeep Jayasumana
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2020 – today
- 2024
[c16]Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit, Daniel Glasner, Ayan Chakrabarti, Sanjiv Kumar:
Rethinking FID: Towards a Better Evaluation Metric for Image Generation. CVPR 2024: 9307-9315- [c15]Sadeep Jayasumana, Daniel Glasner, Srikumar Ramalingam, Andreas Veit, Ayan Chakrabarti, Sanjiv Kumar:
MarkovGen: Structured Prediction for Efficient Text-to-Image Generation. CVPR 2024: 9316-9325 - [c14]Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Wittawat Jitkrittum, Veeranjaneyulu Sadhanala, Sadeep Jayasumana, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar:
USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval. ICML 2024 - [i18]Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit, Daniel Glasner, Ayan Chakrabarti, Sanjiv Kumar:
Rethinking FID: Towards a Better Evaluation Metric for Image Generation. CoRR abs/2401.09603 (2024) - [i17]Ziwei Ji, Himanshu Jain, Andreas Veit, Sashank J. Reddi, Sadeep Jayasumana, Ankit Singh Rawat, Aditya Krishna Menon, Felix Yu, Sanjiv Kumar:
Efficient Document Ranking with Learnable Late Interactions. CoRR abs/2406.17968 (2024) - 2023
- [i16]Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Sadeep Jayasumana, Veeranjaneyulu Sadhanala, Wittawat Jitkrittum, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar:
EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval. CoRR abs/2301.12005 (2023) - [i15]Sadeep Jayasumana, Daniel Glasner, Srikumar Ramalingam, Andreas Veit, Ayan Chakrabarti, Sanjiv Kumar:
SPEGTI: Structured Prediction for Efficient Generative Text-to-Image Models. CoRR abs/2308.10997 (2023) - 2022
- [c13]Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar:
In defense of dual-encoders for neural ranking. ICML 2022: 15376-15400 - [i14]Arslan Chaudhry, Aditya Krishna Menon, Andreas Veit, Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar:
When does mixup promote local linearity in learned representations? CoRR abs/2210.16413 (2022) - 2021
- [c12]Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar:
Long-tail learning via logit adjustment. ICLR 2021 - [c11]Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar:
Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces. ICML 2021: 8890-8901 - [i13]Srikumar Ramalingam, Daniel Glasner, Kaushal Patel, Raviteja Vemulapalli, Sadeep Jayasumana, Sanjiv Kumar:
Balancing Constraints and Submodularity in Data Subset Selection. CoRR abs/2104.12835 (2021) - [i12]Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar:
Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces. CoRR abs/2105.05736 (2021) - 2020
- [c10]Sadeep Jayasumana, Kanchana Ranasinghe, Sahan Liyanaarachchi, Mayuka Jayawardhana, Harsha Ranasinghe, Sina Samangooei:
Bipartite Conditional Random Fields for Panoptic Segmentation. BMVC 2020 - [i11]Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar:
Long-tail learning via logit adjustment. CoRR abs/2007.07314 (2020) - [i10]Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar:
Kernelized Classification in Deep Networks. CoRR abs/2012.09607 (2020)
2010 – 2019
- 2019
- [i9]Sadeep Jayasumana, Kanchana Ranasinghe, Mayuka Jayawardhana, Sahan Liyanaarachchi, Harsha Ranasinghe:
Bipartite Conditional Random Fields for Panoptic Segmentation. CoRR abs/1912.05307 (2019) - 2018
- [j2]Anurag Arnab, Shuai Zheng
, Sadeep Jayasumana, Bernardino Romera-Paredes, Måns Larsson, Alexander Kirillov, Bogdan Savchynskyy, Carsten Rother, Fredrik Kahl, Philip H. S. Torr:
Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction. IEEE Signal Process. Mag. 35(1): 37-52 (2018) - 2016
- [c9]Anurag Arnab, Sadeep Jayasumana, Shuai Zheng, Philip H. S. Torr:
Higher Order Conditional Random Fields in Deep Neural Networks. ECCV (2) 2016: 524-540 - 2015
- [j1]Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi:
Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels. IEEE Trans. Pattern Anal. Mach. Intell. 37(12): 2464-2477 (2015) - [c8]Saumya Jetley, Bernardino Romera-Paredes, Sadeep Jayasumana, Philip H. S. Torr:
Prototypical Priors: From Improving Classification to Zero-Shot Learning. BMVC 2015: 120.1-120.12 - [c7]Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, Philip H. S. Torr:
Conditional Random Fields as Recurrent Neural Networks. ICCV 2015: 1529-1537 - [i8]Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, Philip H. S. Torr:
Conditional Random Fields as Recurrent Neural Networks. CoRR abs/1502.03240 (2015) - [i7]Anurag Arnab, Sadeep Jayasumana, Shuai Zheng, Philip H. S. Torr:
Higher Order Potentials in End-to-End Trainable Conditional Random Fields. CoRR abs/1511.08119 (2015) - [i6]Saumya Jetley, Bernardino Romera-Paredes, Sadeep Jayasumana, Philip H. S. Torr:
Prototypical Priors: From Improving Classification to Zero-Shot Learning. CoRR abs/1512.01192 (2015) - 2014
- [c6]Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi:
Optimizing over Radial Kernels on Compact Manifolds. CVPR 2014: 3802-3809 - [c5]Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Sadeep Jayasumana, Richard I. Hartley, Hongdong Li:
Expanding the Family of Grassmannian Kernels: An Embedding Perspective. ECCV (7) 2014: 408-423 - [i5]Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Sadeep Jayasumana, Richard I. Hartley, Hongdong Li:
Expanding the Family of Grassmannian Kernels: An Embedding Perspective. CoRR abs/1407.1123 (2014) - [i4]Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi:
Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels. CoRR abs/1412.0265 (2014) - [i3]Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi:
Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices. CoRR abs/1412.4172 (2014) - [i2]Sadeep Jayasumana, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi:
A Framework for Shape Analysis via Hilbert Space Embedding. CoRR abs/1412.4174 (2014) - [i1]Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi:
Optimizing Over Radial Kernels on Compact Manifolds. CoRR abs/1412.4175 (2014) - 2013
- [c4]Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi:
Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices. CVPR 2013: 73-80 - [c3]Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi:
Combining Multiple Manifold-Valued Descriptors for Improved Object Recognition. DICTA 2013: 1-6 - [c2]Sadeep Jayasumana, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi:
A Framework for Shape Analysis via Hilbert Space Embedding. ICCV 2013: 1249-1256 - [c1]Hiranya Jayathilaka, Pradeep R. Fernando, Paul Fremantle, Kasun Indrasiri, Dushan Abeyruwan, Supun Kamburugamuve, Sadeep Jayasumana, Sanjiva Weerawarana, Srinath Perera:
Improved Server Architecture for Highly Efficient Message Mediation. iiWAS 2013: 418
Coauthor Index
aka: Mehrtash Tafazzoli Harandi
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