News (December 2021)

• I am giving an invited talk at NeurIPS 2021 DGM workshop.

• One paper is going to appear at NeurIPS 2021.

• I finished a wonderful summer research internship at NVIDIA Applied Deep Learning Research.

Research

Papers on Generative Models

• Zhifeng Kong, Kamalika Chaudhuri. Understanding Instance-based Interpretability of Variational Auto-Encoders. In NeurIPS 2021. [paper] [code] [video] [blog]

• Zhifeng Kong, Wei Ping. On Fast Sampling of Diffusion Probabilistic Models. ArXiv preprint. [paper] [demo] [code]

• Zhifeng Kong, Kamalika Chaudhuri. Universal Approximation of Residual Flows in Maximum Mean Discrepancy. In ICML 2021 INNF Workshop. [paper] [video]

• Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, Bryan Catanzaro. DiffWave: A Versatile Diffusion Model for Audio Synthesis. In ICLR 2021 (oral). [paper] [demo] [video]

• Zhifeng Kong, Kamalika Chaudhuri. The Expressive Power of a Class of Normalizing Flow Models. In AISTATS 2020. [paper] [slides] [blog]

• Zhifeng Kong, Kamalika Chaudhuri. The Expressive Power of Planar Flows. In The Workshop on Theory of Deep Learning: Where next? [paper] [slides] [poster] [video]

Other Papers

• Zhangyu Wang, Lantian Xu, Zhifeng Kong, Weilong Wang, Xuyu Peng, Enyang Zheng. A Geometry-Aware Algorithm to Learn Hierarchical Embeddings in Hyperbolic Space. In ICLR 2021 GTRL Workshop. [paper]

• Zhaoyang Lyu, Ching-Yun Ko, Zhifeng Kong, Ngai Wong, Dahua Lin, Luca Daniel. Fastened CROWN: Tightened Neural Network Robustness Certificates. In AAAI 2020. [paper]

• Zhifeng Kong. Convergence Analysis of Training Two-hidden-layer Partially Over-parameterized ReLU Networks vis Gradient Descent. In ICNIP 2020. [paper]

• Zhifeng Kong. Convergence Analysis of the Dynamics of a Special Kind of Two-Layered Neural Networks with l1 and l2 Regularization. [paper]

• Xingyu Wan, Qing Zhao, Jinjun Wang, Shunming Deng, Zhifeng Kong. Multi-Object Tracking Using Online Metric Learning with Long Short-Term Memory. In IEEE ICIP 2018, 788-792. [paper]

Blogs and Technical Reports

• Understanding Instance-based Interpretability of Variational Auto-Encoders. [blog]

• The expressive power of a class of normalizing flow models. [blog]

• Generalization theory for GANs. [slides]

• Notes on generalization properties of GAN metrics. [paper]

• Invertible ResNets. [slides]

Zhihu Blogs

UCSD Machine Learning Blogs

Talks and Presentations

• I am giving a poster presentation at NeurIPS (December 2021). [video]

• I am giving an invited talk at NeurIPS DGM workshop (December 2021). [video]

• I am giving a talk at UCSD AI seminar (November 2021).

• I am giving two spotlight presentations at ICML INNF workshop (July 2021).

• I am giving a spotlight presentation at ICML XAI workshop (July 2021).

• I am giving an invited talk at NVIDIA (June 2021).

• I am giving an invited talk at AI-Time, an AI community (June 2021).

• I am giving an oral presentation at ICLR 2021 (May 2021). [video]

• I am giving invited talks at TechBeat, an AI community (May 2021). [video]

• I am giving a spotlight presentation at AAAI 2020 (Feb 2020).

• I am giving a spotlight presentation at the IAS deep learning theory workshop (Oct 2019). [video]

Contact me!

Email: z4kong at eng dot ucsd dot edu

WeChat: kong-zhi-feng

Twitter: @ZhifengKong

LinkedIn: Zhifeng Kong

Instagram: zhifeng.kong.3

Zhihu: Zhifeng