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ORCIDKe Li 0011
Person information
- affiliation: University of California, Berkeley, USA
Other persons with the same name
- Ke Li — disambiguation page
- Ke Li 0001
![[0000-0001-7200-4244]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-7200-4244")
— University of Exeter, College of Engineering, Mathematics and Physical Sciences, UK (and 4 more) - Ke Li 0002 — Shandong University, School of Control Science and Engineering, Jinan, China (and 1 more)
- Ke Li 0003 — Beijing Union University, College of Information Technology, China (and 2 more)
- Ke Li 0004 — Beijing University of Posts and Telecommunications, School of Information and Communication Engineering, China
- Ke Li 0005 — PLA Strategic Support Force Information Engineering University, China (and 1 more)
- Ke Li 0006 — Xidian University, School of Physics and Optoelectronic Engineering, Xi'an, China
- Ke Li 0007 — Shandong University, School of Control Science and Engineering, Jinan, China
- Ke Li 0008 — University of Southampton, Optoelectronics Research Centre, UK
- Ke Li 0009 — Heriot-Watt University, Edinburgh, UK
- Ke Li 0010 — Fudan University, Shanghai Key Laboratory of Intelligent Information Processing, China
- Kenneth Li 0002 (aka: Ke Li 0012) — Harvard University, MA, USA
- Ke Li 0013 — Cornell University, Ithaca, NY, USA
- Ke Li 0014 — Sorbonne University, France
- Ke Li 0015 — Tencent Youtu Lab, Shanghai, China
- Ke Li 0016 — Harbin Institute of Technology, Institute for Advanced Study in Mathematics, Nangang, China (and 1 more)
- Ke Li 0017 — Naval University of Engineering, Electronic Engineering Institute, China
- Ke Li 0018 — Facebook AI, Menlo Park, CA, USA (and 1 more)
- Ke Li 0019 — University of Electronic Science and Technology of China, Chengdu, China
- Ke Li 0020 — Southwest Jiaotong University, School of Computing and Artificial Intelligence, Chengdu, China (and 1 more)
- Ke Li 0021 — ETH Zurich, Department of Information Technology and Electrical Engineering, Zürich, Switzerland
- Ke Li 0022 — New York University, Courant Institute, NY, USA
- Ke Li 0023 — Meta AI, Menlo Park, CA, USA (and 1 more)
- Ke Li 0024 — Xidian University, School of Computer Science and Technology, Key Laboratory of Smart Human-Computer Interaction and Wearable Technology, Shaanxi, China
Other persons with a similar name
- Ke-Li Cheng
- Ke-Li Han
- Li-Ke Huang
- Li Ke — disambiguation page
- Li Ke 0001 — Shenyang University of Technology, College of Electrical Engineering, Institute of Biomedical and Electromagnetic Engineering, China
- Ke-Xin Li
- Kebo Li (aka: Ke-Bo Li)
- Kejun Li (aka: Ke-Jun Li)
- Yu-Ke Li
- Like Wang (aka: Li-Ke Wang)
- show all similar names
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2020 – today
- 2024
[c23]Shichong Peng, Yanshu Zhang, Ke Li:
PAPR in Motion: Seamless Point-level 3D Scene Interpolation. CVPR 2024: 21007-21016- [c22]Chirag Vashist, Shichong Peng, Ke Li:
Rejection Sampling IMLE: Designing Priors for Better Few-Shot Image Synthesis. ECCV (21) 2024: 441-456 - [c21]Yuzhen Mao, Martin Ester, Ke Li:
IceFormer: Accelerated Inference with Long-Sequence Transformers on CPUs. ICLR 2024 - [i36]Kiyohiro Nakayama, Mikaela Angelina Uy, Yang You, Ke Li, Leonidas J. Guibas:
ProvNeRF: Modeling per Point Provenance in NeRFs as a Stochastic Process. CoRR abs/2401.08140 (2024) - [i35]Yuzhen Mao, Martin Ester, Ke Li:
IceFormer: Accelerated Inference with Long-Sequence Transformers on CPUs. CoRR abs/2405.02842 (2024) - [i34]Alireza Moazeni, Shichong Peng, Ke Li:
Intrinsic PAPR for Point-level 3D Scene Albedo and Shading Editing. CoRR abs/2407.00500 (2024) - [i33]Chirag Vashist, Shichong Peng, Ke Li:
Rejection Sampling IMLE: Designing Priors for Better Few-Shot Image Synthesis. CoRR abs/2409.17439 (2024) - 2023
- [c20]Mikaela Angelina Uy, Ricardo Martin-Brualla, Leonidas J. Guibas, Ke Li:
SCADE: NeRFs from Space Carving with Ambiguity-Aware Depth Estimates. CVPR 2023: 16518-16527 - [c19]George Kiyohiro Nakayama, Mikaela Angelina Uy, Jiahui Huang, Shi-Min Hu, Ke Li, Leonidas J. Guibas:
DiffFacto: Controllable Part-Based 3D Point Cloud Generation with Cross Diffusion. ICCV 2023: 14211-14221 - [c18]Mehran Aghabozorgi, Shichong Peng, Ke Li:
Adaptive IMLE for Few-shot Pretraining-free Generative Modelling. ICML 2023: 248-264 - [c17]Mikaela Angelina Uy, Kiyohiro Nakayama, Guandao Yang, Rahul Krishna Thomas, Leonidas J. Guibas, Ke Li:
NeRF Revisited: Fixing Quadrature Instability in Volume Rendering. NeurIPS 2023 - [c16]Yanshu Zhang, Shichong Peng, Alireza Moazeni, Ke Li:
PAPR: Proximity Attention Point Rendering. NeurIPS 2023 - [i32]Mikaela Angelina Uy, Ricardo Martin-Brualla, Leonidas J. Guibas, Ke Li:
SCADE: NeRFs from Space Carving with Ambiguity-Aware Depth Estimates. CoRR abs/2303.13582 (2023) - [i31]Alexia Jolicoeur-Martineau, Kilian Fatras, Ke Li, Tal Kachman:
Diffusion models with location-scale noise. CoRR abs/2304.05907 (2023) - [i30]Kiyohiro Nakayama, Mikaela Angelina Uy, Jiahui Huang, Shi-Min Hu, Ke Li, Leonidas J. Guibas:
DiffFacto: Controllable Part-Based 3D Point Cloud Generation with Cross Diffusion. CoRR abs/2305.01921 (2023) - [i29]Yanshu Zhang, Shichong Peng, Alireza Moazeni, Ke Li:
PAPR: Proximity Attention Point Rendering. CoRR abs/2307.11086 (2023) - [i28]Mikaela Angelina Uy, Kiyohiro Nakayama, Guandao Yang, Rahul Krishna Thomas, Leonidas J. Guibas, Ke Li:
NeRF Revisited: Fixing Quadrature Instability in Volume Rendering. CoRR abs/2310.20685 (2023) - [i27]Shichong Peng, Alireza Moazeni, Ke Li:
How Good Are Deep Generative Models for Solving Inverse Problems? CoRR abs/2312.12691 (2023) - 2022
- [c15]Kiarash Zahirnia, Oliver Schulte, Ke Li, Ankita Sakhuja, Parmis Naddaf:
Deep Learning of Latent Edge Types from Relational Data. Canadian AI 2022 - [c14]Himanshu Arora, Saurabh Mishra, Shichong Peng, Ke Li, Ali Mahdavi-Amiri:
Multimodal Shape Completion via Implicit Maximum Likelihood Estimation. CVPR Workshops 2022: 2957-2966 - [c13]Shichong Peng, Seyed Alireza Moazenipourasil, Ke Li:
CHIMLE: Conditional Hierarchical IMLE for Multimodal Conditional Image Synthesis. NeurIPS 2022 - [c12]Kiarash Zahirnia, Oliver Schulte, Parmis Naddaf, Ke Li:
Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders. NeurIPS 2022 - [i26]Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard S. Zemel, Alireza Makhzani:
Variational Model Inversion Attacks. CoRR abs/2201.10787 (2022) - [i25]Kiarash Zahirnia, Oliver Schulte, Parmis Naddaf, Ke Li:
Micro and Macro Level Graph Modeling for Graph Variational Auto-Encoders. CoRR abs/2210.16844 (2022) - [i24]Shichong Peng, Alireza Moazeni, Ke Li:
CHIMLE: Conditional Hierarchical IMLE for Multimodal Conditional Image Synthesis. CoRR abs/2211.14286 (2022) - 2021
- [c11]Daniel Rebain, Wei Jiang, Soroosh Yazdani, Ke Li, Kwang Moo Yi, Andrea Tagliasacchi:
DeRF: Decomposed Radiance Fields. CVPR 2021: 14153-14161 - [c10]Kuan-Chieh Wang, Yan Fu, Ke Li, Ashish Khisti, Richard S. Zemel, Alireza Makhzani:
Variational Model Inversion Attacks. NeurIPS 2021: 9706-9719 - [i23]Alexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer, Tal Kachman, Ioannis Mitliagkas:
Gotta Go Fast When Generating Data with Score-Based Models. CoRR abs/2105.14080 (2021) - [i22]Daniel Rebain, Ke Li, Vincent Sitzmann, Soroosh Yazdani, Kwang Moo Yi, Andrea Tagliasacchi:
Deep Medial Fields. CoRR abs/2106.03804 (2021) - [i21]Shichong Peng, Alireza Moazeni, Ke Li:
Cascading Modular Network (CAM-Net) for Multimodal Image Synthesis. CoRR abs/2106.09015 (2021) - [i20]Kiarash Zahirnia, Ankita Sakhuja, Oliver Schulte, Parmis Nadaf, Ke Li, Xia Hu:
Generating the Graph Gestalt: Kernel-Regularized Graph Representation Learning. CoRR abs/2106.15239 (2021) - [i19]Himanshu Arora, Saurabh Mishra, Shichong Peng, Ke Li, Ali Mahdavi-Amiri:
Shape Completion via IMLE. CoRR abs/2106.16237 (2021) - 2020
- [j1]Ke Li, Shichong Peng, Tianhao Zhang, Jitendra Malik:
Multimodal Image Synthesis with Conditional Implicit Maximum Likelihood Estimation. Int. J. Comput. Vis. 128(10): 2607-2628 (2020) - [c9]Ning Yu, Ke Li, Peng Zhou, Jitendra Malik, Larry Davis, Mario Fritz:
Inclusive GAN: Improving Data and Minority Coverage in Generative Models. ECCV (22) 2020: 377-393 - [i18]Ning Yu, Ke Li, Peng Zhou, Jitendra Malik, Larry Davis, Mario Fritz:
Inclusive GAN: Improving Data and Minority Coverage in Generative Models. CoRR abs/2004.03355 (2020) - [i17]Ke Li, Shichong Peng, Tianhao Zhang, Jitendra Malik:
Multimodal Image Synthesis with Conditional Implicit Maximum Likelihood Estimation. CoRR abs/2004.03590 (2020) - [i16]Shichong Peng, Ke Li:
Generating Unobserved Alternatives. CoRR abs/2011.01926 (2020) - [i15]Daniel Rebain, Wei Jiang, Soroosh Yazdani, Ke Li, Kwang Moo Yi, Andrea Tagliasacchi:
DeRF: Decomposed Radiance Fields. CoRR abs/2011.12490 (2020) - [i14]Ke Li, Shichong Peng, Kailas Vodrahalli, Jitendra Malik:
Better Knowledge Retention through Metric Learning. CoRR abs/2011.13149 (2020)
2010 – 2019
- 2019
- [b1]Ke Li:
Advances in Machine Learning: Nearest Neighbour Search, Learning to Optimize and Generative Modelling. University of California, Berkeley, USA, 2019 - [c8]Yedid Hoshen, Ke Li, Jitendra Malik:
Non-Adversarial Image Synthesis With Generative Latent Nearest Neighbors. CVPR 2019: 5811-5819 - [c7]Ke Li, Tianhao Zhang, Jitendra Malik:
Diverse Image Synthesis From Semantic Layouts via Conditional IMLE. ICCV 2019: 4219-4228 - [c6]Ke Li, Tianhao Zhang, Jitendra Malik:
Approximate Feature Collisions in Neural Nets. NeurIPS 2019: 15816-15824 - [i13]Jianqiao Wangni, Ke Li, Jianbo Shi, Jitendra Malik:
Trajectory Normalized Gradients for Distributed Optimization. CoRR abs/1901.08227 (2019) - 2018
- [i12]Ke Li, Jitendra Malik:
Implicit Maximum Likelihood Estimation. CoRR abs/1809.09087 (2018) - [i11]Ke Li, Shichong Peng, Jitendra Malik:
Super-Resolution via Conditional Implicit Maximum Likelihood Estimation. CoRR abs/1810.01406 (2018) - [i10]Ke Li, Tianhao Zhang, Jitendra Malik:
Diverse Image Synthesis from Semantic Layouts via Conditional IMLE. CoRR abs/1811.12373 (2018) - [i9]Ke Li, Jitendra Malik:
On the Implicit Assumptions of GANs. CoRR abs/1811.12402 (2018) - [i8]Kailas Vodrahalli, Ke Li, Jitendra Malik:
Are All Training Examples Created Equal? An Empirical Study. CoRR abs/1811.12569 (2018) - 2017
- [c5]Ke Li, Jitendra Malik:
Learning to Optimize. ICLR (Poster) 2017 - [c4]Ke Li, Jitendra Malik:
Fast k-Nearest Neighbour Search via Prioritized DCI. ICML 2017: 2081-2090 - [i7]Ke Li, Jitendra Malik:
Fast k-Nearest Neighbour Search via Prioritized DCI. CoRR abs/1703.00440 (2017) - [i6]Ke Li, Jitendra Malik:
Learning to Optimize Neural Nets. CoRR abs/1703.00441 (2017) - 2016
- [c3]Ke Li, Bharath Hariharan, Jitendra Malik:
Iterative Instance Segmentation. CVPR 2016: 3659-3667 - [c2]Ke Li, Jitendra Malik:
Amodal Instance Segmentation. ECCV (2) 2016: 677-693 - [c1]Ke Li, Jitendra Malik:
Fast k-Nearest Neighbour Search via Dynamic Continuous Indexing. ICML 2016: 671-679 - [i5]Ke Li, Jitendra Malik:
Amodal Instance Segmentation. CoRR abs/1604.08202 (2016) - [i4]Ke Li, Jitendra Malik:
Learning to Optimize. CoRR abs/1606.01885 (2016) - 2015
- [i3]Ke Li, Jitendra Malik:
Bandit Label Inference for Weakly Supervised Learning. CoRR abs/1509.06807 (2015) - [i2]Ke Li, Bharath Hariharan, Jitendra Malik:
Iterative Instance Segmentation. CoRR abs/1511.08498 (2015) - [i1]Ke Li, Jitendra Malik:
Fast k-Nearest Neighbour Search via Dynamic Continuous Indexing. CoRR abs/1512.00442 (2015)
Coauthor Index
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