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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

You can also find my artist page

Mash-up live: Don’t Ask (cover J.sheon), Maze (cover step.jad), Gorilla (cover Bruno Mars)

Involved in the production of the theme song - which means you can hear my voice in the movie!

Live: Someone like you (cover Adele)

An uncertainty-aware flow-matching framework that uses test-time search to generate playable virtual instruments with consistent timbre across pitches and velocities.

A Dockerized, DAW-powered pipeline for generating realistic multitrack datasets with heterogeneous audio-effects graphs and commercial plugins.

Focusing on the application of probabilistic and statistical principles to generative modeling, this sharing explores the connections between different generative models in a statistical learning framework, including score-based and flow-based generative models, in a step-by-step manner. Sharing will start with basic concepts to ensure the audience understands the required math, providing intuitive explanations as they progress into key theories. Finally, based on an in-depth analysis of existing work on generative modeling, the sharing suggests guidelines that can help with theoretical machine learning research, aiming to provide practical implications for participants.