Bin Dai

Xiaomi (China) — China

Computer Science · Physical Sciences

10h-index416citations24works1.32yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Generative Adversarial Networks and Image Synthesis(9), Model Reduction and Neural Networks(3), Music and Audio Processing(3), Anomaly Detection Techniques and Applications(3), Natural Language Processing Techniques(2)

Publications24 total

Disentangling Planning, Driving and Rendering for Photorealistic Avatar Agents
Lecture notes in computer science·2025· 4 cited
Towards Objectively Benchmarking Social Intelligence for Language Agents at Action Level
arXiv (Cornell University)·2024Open Access
Towards Objectively Benchmarking Social Intelligence of Language Agents at the Action Level
2024Open Access
Risk assessment of passenger flow dispersion in urban rail transit transfer stations
IET conference proceedings.·2023· 1 cited
On the Value of Infinite Gradients in Variational Autoencoder Models
Neural Information Processing Systems·2021· 2 cited
Understanding the Role of Self-Supervised Learning in Out-of-Distribution Detection Task
arXiv (Cornell University)·2021Open Access
Amplitude effect on micro-hole drilling of 3D needled Cf/SiC by ultrasonic vibration
Ceramics International·2021· 21 cited
Innovative Formation Tester Sampling Procedures for Carbon Dioxide and Other Reactive Components
Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description·2021· 1 cited
Further Analysis of Outlier Detection with Deep Generative Models
arXiv (Cornell University)·2020· 10 citedOpen Access
Further Analysis of Outlier Detection with Deep Generative Models
Neural Information Processing Systems·2020· 6 cited
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
arXiv (Cornell University)·2019· 28 citedOpen Access
Formation Fluid Microsampling While Drilling: A New PVT and Geochemical Formation Evaluation Technique
SPE Annual Technical Conference and Exhibition·2019· 2 cited
Diagnosing and Enhancing VAE Models
arXiv (Cornell University)·2019· 95 citedOpen Access
Recurrent Variational Autoencoders for Learning Nonlinear Generative Models in the Presence of Outliers
IEEE Journal of Selected Topics in Signal Processing·2018· 19 citedOpen Access
Compressing Neural Networks using the Variational Information Bottleneck.
International Conference on Machine Learning·2018· 76 cited
Hydrogen Sulfide Gas Detection via Multivariate Optical Computing
Sensors·2018· 22 citedOpen Access
Compressing Neural Networks using the Variational Information Bottleneck
arXiv (Cornell University)·2018· 71 citedOpen Access
Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models
Journal of Machine Learning Research·2018· 36 cited
Understanding and Predicting The Attractiveness of Human Action Shot
arXiv (Cornell University)·2017· 1 citedOpen Access
Veiled Attributes of the Variational Autoencoder.
arXiv (Cornell University)·2017· 1 citedOpen Access
page 1 of 2Next →

Frequent Co-authors

David Wipf(12), John A. D. Aston(5), Gang Hua(5), Baoyuan Wang(4), Christopher Jones(3), Megan Pearl(2), Yu Wang(2), Ziyu Wang(2), Jun Zhu(2), Chenxu Wang(2), Huaping Liu(2), Chen Zhu(1), Baining Guo(1), Chen Zhu(1), Yu Wang(1), Ziyu Wang(1), Mickey Pelletier(1), Michael L. Myrick(1), Maoxun Wang(1), Huadong Yu(1)