Dilin Wang

According to our database, Dilin Wang authored at least 43 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

3D Mesh Editing using Masked LRMs.

Will Gao, Dilin Wang, Yuchen Fan, Aljaz Bozic, Tuur Stuyck, Zhengqin Li, Zhao Dong, Rakesh Ranjan, Nikolaos Sarafianos

CoRR, 2024

MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 Seconds.

Zhenggang Tang, Yuchen Fan, Dilin Wang, Hongyu Xu, Rakesh Ranjan, Alexander Schwing, Zhicheng Yan

CoRR, 2024

SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identity.

Peihao Wang, Zhiwen Fan, Dejia Xu, Dilin Wang, Sreyas Mohan, Forrest N. Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu, Zhangyang Wang, Vikas Chandra

CoRR, 2024

Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once.

Zhangheng Li, Shiwei Liu, Tianlong Chen, Ajay Kumar Jaiswal, Zhenyu Zhang, Dilin Wang, Raghuraman Krishnamoorthi, Shiyu Chang, Zhangyang Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T Compression For On-Device ASR Models.

Yuan Shangguan, Haichuan Yang, Danni Li, Chunyang Wu, Yassir Fathullah, Dilin Wang, Ayushi Dalmia, Raghuraman Krishnamoorthi, Ozlem Kalinli, Junteng Jia, Jay Mahadeokar, Xin Lei, Mike Seltzer, Vikas Chandra

Proceedings of the IEEE International Conference on Acoustics, 2024

MVDiffusion++: A Dense High-Resolution Multi-view Diffusion Model for Single or Sparse-View 3D Object Reconstruction.

Shitao Tang, Jiacheng Chen, Dilin Wang, Chengzhou Tang, Fuyang Zhang, Yuchen Fan, Vikas Chandra, Yasutaka Furukawa, Rakesh Ranjan

Proceedings of the Computer Vision - ECCV 2024, 2024

POCA: Post-training Quantization with Temporal Alignment for Codec Avatars.

Jian Meng, Yuecheng Li, Chenghui Li, Syed Shakib Sarwar, Dilin Wang, Jae-sun Seo

Proceedings of the Computer Vision - ECCV 2024, 2024

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything.

Yunyang Xiong, Bala Varadarajan, Lemeng Wu, Xiaoyu Xiang, Fanyi Xiao, Chenchen Zhu, Xiaoliang Dai, Dilin Wang, Fei Sun, Forrest N. Iandola, Raghuraman Krishnamoorthi, Vikas Chandra

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Taming Mode Collapse in Score Distillation for Text-to-3D Generation.

Peihao Wang, Dejia Xu, Zhiwen Fan, Dilin Wang, Sreyas Mohan, Forrest N. Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu, Zhangyang Wang, Vikas Chandra

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts.

Ganesh Jawahar, Haichuan Yang, Yunyang Xiong, Zechun Liu, Dilin Wang, Fei Sun, Meng Li, Aasish Pappu, Barlas Oguz, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Raghuraman Krishnamoorthi, Vikas Chandra

Proceedings of the Findings of the Association for Computational Linguistics, 2024

PathFusion: Path-Consistent Lidar-Camera Deep Feature Fusion.

Lemeng Wu, Dilin Wang, Meng Li, Yunyang Xiong, Raghuraman Krishnamoorthi, Qiang Liu, Vikas Chandra

Proceedings of the International Conference on 3D Vision, 2024

2023

Drag View: Generalizable Novel View Synthesis with Unposed Imagery.

Zhiwen Fan, Panwang Pan, Peihao Wang, Yifan Jiang, Hanwen Jiang, Dejia Xu, Zehao Zhu, Dilin Wang, Zhangyang Wang

CoRR, 2023

Temporally Consistent Online Depth Estimation in Dynamic Scenes.

Zhaoshuo Li, Wei Ye, Dilin Wang, Francis X. Creighton, Russell H. Taylor, Ganesh Venkatesh, Mathias Unberath

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Fast Point Cloud Generation with Straight Flows.

Lemeng Wu, Dilin Wang, Chengyue Gong, Xingchao Liu, Yunyang Xiong, Rakesh Ranjan, Raghuraman Krishnamoorthi, Vikas Chandra, Qiang Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training.

Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra

Proceedings of the Tenth International Conference on Learning Representations, 2022

Omni-Sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR Via Supernet.

Haichuan Yang, Yuan Shangguan, Dilin Wang, Meng Li, Pierce Chuang, Xiaohui Zhang, Ganesh Venkatesh, Ozlem Kalinli, Vikas Chandra

Proceedings of the IEEE International Conference on Acoustics, 2022

Streaming Transformer Transducer based Speech Recognition Using Non-Causal Convolution.

Yangyang Shi, Chunyang Wu, Dilin Wang, Alex Xiao, Jay Mahadeokar, Xiaohui Zhang, Chunxi Liu, Ke Li, Yuan Shangguan, Varun Nagaraja, Ozlem Kalinli, Mike Seltzer

Proceedings of the IEEE International Conference on Acoustics, 2022

Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation.

Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Z. Pan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Noisy Training Improves E2E ASR for the Edge.

Dilin Wang, Yuan Shangguan, Haichuan Yang, Pierce Chuang, Jiatong Zhou, Meng Li, Ganesh Venkatesh, Ozlem Kalinli, Vikas Chandra

CoRR, 2021

Improve Vision Transformers Training by Suppressing Over-smoothing.

Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu

CoRR, 2021

AlphaNet: Improved Training of Supernet with Alpha-Divergence.

Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra

CoRR, 2021

AlphaNet: Improved Training of Supernets with Alpha-Divergence.

Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra

Proceedings of the 38th International Conference on Machine Learning, 2021

AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling.

Dilin Wang, Meng Li, Chengyue Gong, Vikas Chandra

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

KeepAugment: A Simple Information-Preserving Data Augmentation Approach.

Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

AlphaMatch: Improving Consistency for Semi-Supervised Learning With Alpha-Divergence.

Chengyue Gong, Dilin Wang, Qiang Liu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2019

Energy-Aware Neural Architecture Optimization with Fast Splitting Steepest Descent.

Dilin Wang, Meng Li, Lemeng Wu, Vikas Chandra, Qiang Liu

CoRR, 2019

Splitting Steepest Descent for Growing Neural Architectures.

Lemeng Wu, Dilin Wang, Qiang Liu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Stein Variational Gradient Descent With Matrix-Valued Kernels.

Dilin Wang, Ziyang Tang, Chandrajit Bajaj, Qiang Liu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Improving Neural Language Modeling via Adversarial Training.

Dilin Wang, ChengYue Gong, Qiang Liu

Proceedings of the 36th International Conference on Machine Learning, 2019

Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models.

Dilin Wang, Qiang Liu

Proceedings of the 36th International Conference on Machine Learning, 2019

Mixed Precision Neural Architecture Search for Energy Efficient Deep Learning.

ChengYue Gong, Zixuan Jiang, Dilin Wang, Yibo Lin, Qiang Liu, David Z. Pan

Proceedings of the International Conference on Computer-Aided Design, 2019

2018

Variational Inference with Tail-adaptive f-Divergence.

Dilin Wang, Hao Liu, Qiang Liu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Stein Variational Gradient Descent as Moment Matching.

Qiang Liu, Dilin Wang

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Stein Variational Message Passing for Continuous Graphical Models.

Dilin Wang, Zhe Zeng, Qiang Liu

Proceedings of the 35th International Conference on Machine Learning, 2018

An Optimization View on Dynamic Routing Between Capsules.

Dilin Wang, Qiang Liu

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Structured Stein Variational Inference for Continuous Graphical Models.

Dilin Wang, Zhe Zeng, Qiang Liu

CoRR, 2017

Learning Deep Energy Models: Contrastive Divergence vs. Amortized MLE.

Qiang Liu, Dilin Wang

CoRR, 2017

Learning to Draw Samples with Amortized Stein Variational Gradient Descent.

Yihao Feng, Dilin Wang, Qiang Liu

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

2016

Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning.

Dilin Wang, Qiang Liu

CoRR, 2016

Efficient Observation Selection in Probabilistic Graphical Models Using Bayesian Lower Bounds.

Dilin Wang, John W. Fisher III, Qiang Liu

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm.

Qiang Liu, Dilin Wang

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Entity Disambiguation by Knowledge and Text Jointly Embedding.

Wei Fang, Jianwen Zhang, Dilin Wang, Zheng Chen, Ming Li

Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, 2016

2013

Fast Algorithm for Approximate k-Nearest Neighbor Graph Construction.

Dilin Wang, Lei Shi, Jianwen Cao

Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013