Marc T. Law

@nmwsharp @nvidia @FidlerSanja Welcome to our team. :)

Some very exciting career news: I've joined @NVIDIA as a scientist to work on the future of 3D geometry, machine learning, and visual computing with @FidlerSanja and many other brilliant folks! Can't wait to share what we create 🚀(1/2)

(1/7) Our #CVPR2022 paper “How Much More Data Do I Need? Estimating Requirements For Downstream Tasks” explores data collection practices! w/ @james_r_lucas @davidjesusacu @lidaiqing @PhilionJonah @ALVAREZ_JOSEM @ZhidingYu @FidlerSanja @MarcTLaw Webpage: nv-tlabs.github.io/estimatingrequ…

How Much More Data Do I Need? Estimating Requirements for Downstream Tasks abs: arxiv.org/abs/2207.01725

@james_r_lucas @nvidia @FidlerSanja Congrats and welcome! It will be our fifth year together in the same teams. 🥳

I'm super excited to share that I'll be joining @nvidia as a research scientist early next year! I feel very fortunate that I can continue to work with such an amazing team, led by @FidlerSanja. I'll be moving back to the UK (!) and I can't wait to start this next chapter.

We just release the f-DAL source code into an easy-to-use library that allows integrating f-DAL with existing pipelines by only changing a few lines of code. Check it out nv-tlabs.github.io/fDAL/.

Excited to share fDAL #ICML2021 We connect theory and algorithms for domain adaptation using a novel f-divergence based bound. fDAL explains existing algorithms, shows their bottlenecks and how to fix them! arxiv.org/abs/2106.11344 w/ @gjzhang1 @MarcTLaw @FidlerSanja @NVIDIAAI