58 citations · 61 across the 8 of their papers we have counts for
8 papers
On Exact Bit-level Reversible Transformers Without Changing Architectures
Guoqiang Zhang, J. P. Lewis, W. B. Kleijn
Various reversible deep neural networks (DNN) models have been proposed to reduce memory consumption in the training process. However, almost all existing reversible DNNs either re…
TrailBlazer: Trajectory Control for Diffusion-Based Video Generation
Wan-Duo Kurt Ma, J. P. Lewis, W. Bastiaan Kleijn
Within recent approaches to text-to-video (T2V) generation, achieving controllability in the synthesized video is often a challenge. Typically, this issue is addressed by providing…
Lookahead Diffusion Probabilistic Models for Refining Mean Estimation
Guoqiang Zhang, Niwa Kenta, W. Bastiaan Kleijn
We propose lookahead diffusion probabilistic models (LA-DPMs) to exploit the correlation in the outputs of the deep neural networks (DNNs) over subsequent timesteps in diffusion pr…
LMCodec: A Low Bitrate Speech Codec With Causal Transformer Models
Teerapat Jenrungrot, Michael Chinen, W. Bastiaan Kleijn +4
We introduce LMCodec, a causal neural speech codec that provides high quality audio at very low bitrates. The backbone of the system is a causal convolutional codec that encodes au…
Estimation of Source and Receiver Positions, Room Geometry and Reflection Coefficients From a Single Room Impulse Response
Wangyang Yu, W. Bastiaan Kleijn
We propose an algorithm to estimate source and receiver positions, room geometry and reflection coefficients from a single room impulse response simultaneously. It is based on a sy…
Ultra-Low-Bitrate Speech Coding with Pretrained Transformers
Ali Siahkoohi, Michael Chinen, Tom Denton +2
Speech coding facilitates the transmission of speech over low-bandwidth networks with minimal distortion. Neural-network based speech codecs have recently demonstrated significant…