Anushree Bannadabhavi
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    Projects

    • Community-Aware Transformer for Autism Prediction in fMRI Connectome

      Selected for the MICCAI 2023 conference

      May 10, 2023

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      Com-BrainTF - A novel local-global hierarchical transformer architecture to efficiently learn and integrate community-aware ROI embeddings for fMRI connectome analysis by utilizing both ROI-level and community-level information. Our paper got accepted in the prestigious MICCAI (The Medical Image Computing and Computer Assisted Intervention Society) 2023 conference. [Read More]
      Tags:
      • transformers
      • fMRI
      • PyTorch
      • wandB
    • DE-TensoRF - Data-Efficient and Fast NeRFs

      Techniques to achieve data-efficiency in NeRFs

      April 20, 2023

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      Developed DE-TensoRF, a model that can render high-quality 3D objects with as few as 3 input images, and in under 15 min on a single GPU. Proposed three techniques to achieve data-effiency: (i) Obtain unseen views using symmetry (ii) Semantic conditioning (iii) Semantic Loss. [Read More]
      Tags:
      • NeRFs
      • NeuralNet
      • PyTorch
    • Orator

      Student Speaking Simulator

      June 30, 2022

      The Student Speaking Simulator creates an immersive room experience using projectors to replicate a live audience, and provides students with the opportunity to practice and develop their speaking skills year-round. The Simulator also records your performance and key metrics, and provides feedback for improvement. Not exclusive to public speaking, the... [Read More]
      Tags:
      • QT
      • Python
      • Minimum Viable Product
    • V-DMGNN-GAN

      Spatial inpainting for Human Motion Prediction

      April 28, 2022

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      Variational seq2seq DMGNN-based GAN (V-DMGNN-GAN) model for human skeletal motion prediction. [Read More]
      Tags:
      • VAE
      • GAN
      • PyTorch
    • An RL bot - Robocode

      Reinforcement Learning agent built with Java

      December 22, 2021

      Built a robocode tank (a Reinforcement Learning agent) that battles with another robot (an enemy) and defeats it ~80% of the time. The error backpropagation algorithm as applied to multi-layer perceptron and reinforcement learning is used for the robot’s attack or defence strategy. [Read More]
      Tags:
      • Reinforcement Learning
      • NeuralNet
      • Java
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    Anushree Bannadabhavi  •  2024

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