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20192024
most citedOptimization of Graph Neural Networks with Natural Gradient Descent

10 citations · 15 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.SD2024

Improving Music Source Separation with Diffusion and Consistency Refinement

Tornike Karchkhadze, Mohammad Rasool Izadi, Shuo Zhang +1

In this work, we propose an approach to music source separation that uses a generative diffusion model as a last-stage refinement on top of a deterministic separator, progressively…

cs.SD2024

Multi-Track MusicLDM: Towards Versatile Music Generation with Latent Diffusion Model

Tornike Karchkhadze, Mohammad Rasool Izadi, Ke Chen +2

Diffusion models have shown promising results in cross-modal generation tasks involving audio and music, such as text-to-sound and text-to-music generation. These text-controlled m…

cs.SD2024

Simultaneous Music Separation and Generation Using Multi-Track Latent Diffusion Models

Tornike Karchkhadze, Mohammad Rasool Izadi, Shlomo Dubnov

Diffusion models have recently shown strong potential in both music generation and music source separation tasks. Although in early stages, a trend is emerging towards integrating…

cs.SD2024

"It is okay to be uncommon": Quantizing Sound Event Detection Networks on Hardware Accelerators with Uncommon Sub-Byte Support

Yushu Wu, Xiao Quan, Mohammad Rasool Izadi +1

If our noise-canceling headphones can understand our audio environments, they can then inform us of important sound events, tune equalization based on the types of content we liste…

eess.AS2024

Latent CLAP Loss for Better Foley Sound Synthesis

Tornike Karchkhadze, Hassan Salami Kavaki, Mohammad Rasool Izadi +5

Foley sound generation, the art of creating audio for multimedia, has recently seen notable advancements through text-conditioned latent diffusion models. These systems use multimo…