28 citations · 57 across the 6 of their papers we have counts for
7 papers
Modeling Perceptual Loudness of Piano Tone: Theory and Applications
Yang Qu, Yutian Qin, Lecheng Chao +3
The relationship between perceptual loudness and physical attributes of sound is an important subject in both computer music and psychoacoustics. Early studies of "equal-loudness c…
Kubric: A scalable dataset generator
Klaus Greff, Francois Belletti, Lucas Beyer +32
Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and trainin…
Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings
Qipeng Guo, Zhijing Jin, Ziyu Wang +5
Cycle-consistent training is widely used for jointly learning a forward and inverse mapping between two domains of interest without the cumbersome requirement of collecting matched…
Further Analysis of Outlier Detection with Deep Generative Models
Ziyu Wang, Bin Dai, David Wipf +1
The recent, counter-intuitive discovery that deep generative models (DGMs) can frequently assign a higher likelihood to outliers has implications for both outlier detection applica…
A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models
Ziyu Wang, Shuyu Cheng, Yueru Li +2
Score matching provides an effective approach to learning flexible unnormalized models, but its scalability is limited by the need to evaluate a second-order derivative. In this pa…
The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
Bin Dai, Ziyu Wang, David Wipf
In narrow asymptotic settings Gaussian VAE models of continuous data have been shown to possess global optima aligned with ground-truth distributions. Even so, it is well known tha…