Dilin Wang

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 55

Top Topics

Variational Inference

Neural Architecture

Graphical Models

Contrastive Divergence

Top Venues

Publications

Peihao Wang, Dejia Xu, Zhiwen Fan, Dilin Wang, Sreyas Mohan, Forrest Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu, Zhangyang Wang, Vikas Chandra
Taming Mode Collapse in Score Distillation for Text-to-3D Generation. CoRR (2024)
Lemeng Wu, Dilin Wang, Meng Li, Yunyang Xiong, Raghuraman Krishnamoorthi, Qiang Liu, Vikas Chandra
PathFusion: Path-Consistent Lidar-Camera Deep Feature Fusion. 3DV (2024)
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
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts. ACL (Findings) (2024)
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
TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T Compression For On-Device ASR Models. ICASSP (2024)
Peihao Wang, Zhiwen Fan, Dejia Xu, Dilin Wang, Sreyas Mohan, Forrest N. Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu, Zhangyang Wang, Vikas Chandra
SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identity. CoRR (2024)
Shitao Tang, Jiacheng Chen, Dilin Wang, Chengzhou Tang, Fuyang Zhang, Yuchen Fan, Vikas Chandra, Yasutaka Furukawa, Rakesh Ranjan
MVDiffusion++: A Dense High-resolution Multi-view Diffusion Model for Single or Sparse-view 3D Object Reconstruction. CoRR (2024)
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
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts. CoRR (2023)
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
TODM: Train Once Deploy Many Efficient Supernet-Based RNN-T Compression For On-device ASR Models. CoRR (2023)
Lemeng Wu, Dilin Wang, Chengyue Gong, Xingchao Liu, Yunyang Xiong, Rakesh Ranjan, Raghuraman Krishnamoorthi, Vikas Chandra, Qiang Liu
Fast Point Cloud Generation with Straight Flows. CVPR (2023)
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
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything. CoRR (2023)
Zhaoshuo Li, Wei Ye, Dilin Wang, Francis X. Creighton, Russell H. Taylor, Ganesh Venkatesh, Mathias Unberath
Temporally Consistent Online Depth Estimation in Dynamic Scenes. WACV (2023)
Zhiwen Fan, Panwang Pan, Peihao Wang, Yifan Jiang, Hanwen Jiang, Dejia Xu, Zehao Zhu, Dilin Wang, Zhangyang Wang
Drag View: Generalizable Novel View Synthesis with Unposed Imagery. CoRR (2023)
Lemeng Wu, Dilin Wang, Chengyue Gong, Xingchao Liu, Yunyang Xiong, Rakesh Ranjan, Raghuraman Krishnamoorthi, Vikas Chandra, Qiang Liu
Fast Point Cloud Generation with Straight Flows. CoRR (2022)
Haichuan Yang, Yuan Shangguan, Dilin Wang, Meng Li, Pierce Chuang, Xiaohui Zhang, Ganesh Venkatesh, Ozlem Kalinli, Vikas Chandra
Omni-Sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR Via Supernet. ICASSP (2022)
Yangyang Shi, Chunyang Wu, Dilin Wang, Alex Xiao, Jay Mahadeokar, Xiaohui Zhang, Chunxi Liu, Ke Li, Yuan Shangguan, Varun Nagaraja, Ozlem Kalinli, Mike Seltzer
Streaming Transformer Transducer based Speech Recognition Using Non-Causal Convolution. ICASSP (2022)
Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training. ICLR (2022)
Lemeng Wu, Dilin Wang, Meng Li, Yunyang Xiong, Raghuraman Krishnamoorthi, Qiang Liu, Vikas Chandra
PathFusion: Path-consistent Lidar-Camera Deep Feature Fusion. CoRR (2022)
Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Z. Pan
Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation. CVPR (2022)
Dilin Wang, Meng Li, Chengyue Gong, Vikas Chandra
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling. CVPR (2021)
Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu
KeepAugment: A Simple Information-Preserving Data Augmentation Approach. CVPR (2021)
Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra
AlphaNet: Improved Training of Supernets with Alpha-Divergence. ICML (2021)
Haichuan Yang, Yuan Shangguan, Dilin Wang, Meng Li, Pierce Chuang, Xiaohui Zhang, Ganesh Venkatesh, Ozlem Kalinli, Vikas Chandra
Omni-sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR via Supernet. CoRR (2021)
Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu
Improve Vision Transformers Training by Suppressing Over-smoothing. CoRR (2021)
Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Z. Pan
Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation. CoRR (2021)
Dilin Wang, Yuan Shangguan, Haichuan Yang, Pierce Chuang, Jiatong Zhou, Meng Li, Ganesh Venkatesh, Ozlem Kalinli, Vikas Chandra
Noisy Training Improves E2E ASR for the Edge. CoRR (2021)
Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra
AlphaNet: Improved Training of Supernet with Alpha-Divergence. CoRR (2021)
Chengyue Gong, Dilin Wang, Qiang Liu
AlphaMatch: Improving Consistency for Semi-Supervised Learning With Alpha-Divergence. CVPR (2021)
Zhaoshuo Li, Wei Ye, Dilin Wang, Francis X. Creighton, Russell H. Taylor, Ganesh Venkatesh, Mathias Unberath
Temporally Consistent Online Depth Estimation in Dynamic Scenes. CoRR (2021)
Yangyang Shi, Chunyang Wu, Dilin Wang, Alex Xiao, Jay Mahadeokar, Xiaohui Zhang, Chunxi Liu, Ke Li, Yuan Shangguan, Varun Nagaraja, Ozlem Kalinli, Mike Seltzer
Streaming Transformer Transducer Based Speech Recognition Using Non-Causal Convolution. CoRR (2021)
Chengyue Gong, Dilin Wang, Qiang Liu
AlphaMatch: Improving Consistency for Semi-supervised Learning with Alpha-divergence. CoRR (2020)
Dilin Wang, Meng Li, Chengyue Gong, Vikas Chandra
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling. CoRR (2020)
Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, Qiang Liu
KeepAugment: A Simple Information-Preserving Data Augmentation Approach. CoRR (2020)
Dilin Wang, Qiang Liu
Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models. ICML (2019)
Qiang Liu, Lemeng Wu, Dilin Wang
Splitting Steepest Descent for Growing Neural Architectures. CoRR (2019)
Dilin Wang, ChengYue Gong, Qiang Liu
Improving Neural Language Modeling via Adversarial Training. CoRR (2019)
Lemeng Wu, Dilin Wang, Qiang Liu
Splitting Steepest Descent for Growing Neural Architectures. NeurIPS (2019)
Dilin Wang, Ziyang Tang, Chandrajit Bajaj, Qiang Liu
Stein Variational Gradient Descent With Matrix-Valued Kernels. CoRR (2019)
Dilin Wang, Ziyang Tang, Chandrajit Bajaj, Qiang Liu
Stein Variational Gradient Descent With Matrix-Valued Kernels. NeurIPS (2019)
ChengYue Gong, Zixuan Jiang, Dilin Wang, Yibo Lin, Qiang Liu, David Z. Pan
Mixed Precision Neural Architecture Search for Energy Efficient Deep Learning. ICCAD (2019)
Dilin Wang, Meng Li, Lemeng Wu, Vikas Chandra, Qiang Liu
Energy-Aware Neural Architecture Optimization with Fast Splitting Steepest Descent. CoRR (2019)
Dilin Wang, ChengYue Gong, Qiang Liu
Improving Neural Language Modeling via Adversarial Training. ICML (2019)
Dilin Wang, Hao Liu, Qiang Liu
Variational Inference with Tail-adaptive f-Divergence. NeurIPS (2018)
Dilin Wang, Zhe Zeng, Qiang Liu
Stein Variational Message Passing for Continuous Graphical Models. ICML (2018)
Dilin Wang, Qiang Liu
An Optimization View on Dynamic Routing Between Capsules. ICLR (Workshop) (2018)
Qiang Liu, Dilin Wang
Stein Variational Gradient Descent as Moment Matching. CoRR (2018)
Dilin Wang, Hao Liu, Qiang Liu
Variational Inference with Tail-adaptive f-Divergence. CoRR (2018)
Qiang Liu, Dilin Wang
Stein Variational Gradient Descent as Moment Matching. NeurIPS (2018)
Dilin Wang, Zhe Zeng, Qiang Liu
Structured Stein Variational Inference for Continuous Graphical Models. CoRR (2017)
Qiang Liu, Dilin Wang
Learning Deep Energy Models: Contrastive Divergence vs. Amortized MLE. CoRR (2017)
Yihao Feng, Dilin Wang, Qiang Liu
Learning to Draw Samples with Amortized Stein Variational Gradient Descent. UAI (2017)
Dilin Wang, John W. Fisher III, Qiang Liu
Efficient Observation Selection in Probabilistic Graphical Models Using Bayesian Lower Bounds. UAI (2016)
Dilin Wang, Qiang Liu
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning. CoRR (2016)
Qiang Liu, Dilin Wang
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm. CoRR (2016)
Qiang Liu, Dilin Wang
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm. NIPS (2016)
Wei Fang, Jianwen Zhang, Dilin Wang, Zheng Chen, Ming Li
Entity Disambiguation by Knowledge and Text Jointly Embedding. CoNLL (2016)
Dilin Wang, Lei Shi, Jianwen Cao
Fast Algorithm for Approximate k-Nearest Neighbor Graph Construction. ICDM Workshops (2013)