Dmytro KuzmenkoPlan-Seq-Learn OverviewThe field of Robotics field is moving forward very rapidly. Tons of research is happening in the directions of 3D point representations…May 9May 9
Dmytro KuzmenkoDeepMind’s Genie — the first foundation world modelWhile making stready progress on my robotics research and drafting my first version of literature review for the dissertation, I come…Feb 271Feb 271
Dmytro KuzmenkoThe current state of things and progress in Robotics and What is to come soonWhat are we seeing nowadays in robotics? Some personal thoughts on the topic and key highlights from DeepMind Robotics team blogpostJan 5Jan 5
Dmytro KuzmenkoIROS paper acceptance: Semi-Supervised Learning in Wearable Robotics publication right on Master’s…An article on my first manuscript on SSL in wearable robotics accepted to IROS 2023.Aug 19, 2023Aug 19, 2023
Dmytro KuzmenkoDiffusion model pathway [chapter I] — Denoising diffusion probabilistic modelsGreetings once again, after a while I am coming back to paper reviews. And what better candidate to select than the buzzing Diffusion…Dec 6, 2022Dec 6, 2022
Dmytro KuzmenkoMega attention breakdownGreetings! I recently talked at the AI House Paper Club on Mega attention — a simple, efficient, and effective neural architecture used as…Oct 8, 2022Oct 8, 2022
Dmytro KuzmenkoGC ViT: Efficient Fusing of Global and Local Self-AttentionFollowing up on my first breakdown of Next-ViT, I want to present and review another novel approach to hybrid Vision Transformers — GC ViT.Aug 19, 2022Aug 19, 2022
Dmytro KuzmenkoNext-ViT: Industrial deployment-friendly SOTA hybrid architecture with great inference and…It has been a while since the last review of mine, but two recent Vision Transformer architectures, GC ViT and Next-ViT, sparked my…Aug 10, 2022Aug 10, 2022
Dmytro KuzmenkoCLIP-Gen: A Self-Supervised Approach for General Text-to-Image Generation.In this paper, the authors propose a self-supervised scheme named CLIP-GEN for general text-to-image generation with the language-image..May 9, 2022May 9, 2022
Dmytro KuzmenkoZeroGen: Efficient Zero-shot Learning via Dataset GenerationAn interesting take on zero-shot learning was introduced in a paper that was dated Feb 16.Apr 29, 2022Apr 29, 2022
![Diffusion model pathway [chapter I] — Denoising diffusion probabilistic models](https://miro.medium.com/v2/resize:fill:160:106/1*ekD1okyXD6JBjVEJvdoZTw.png)
![Diffusion model pathway [chapter I] — Denoising diffusion probabilistic models](https://miro.medium.com/v2/resize:fill:320:214/1*ekD1okyXD6JBjVEJvdoZTw.png)
