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06/28/2023
Reconstructing the Hemodynamic Response Function via a Bimodal Transformer
The relationship between blood flow and neuronal activity is widely reco...
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01/27/2023
Deep Quantum Error Correction
Quantum error correction codes (QECC) are a key component for realizing ...
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09/16/2022
Denoising Diffusion Error Correction Codes
Error correction code (ECC) is an integral part of the physical communic...
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03/27/2022
Error Correction Code Transformer
Error correction code is a major part of the communication physical laye...
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10/28/2021
Meta Subspace Optimization
Subspace optimization methods have the attractive property of reducing l...
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10/26/2021
Geometric Transformer for End-to-End Molecule Properties Prediction
Transformers have become methods of choice in many applications thanks t...
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08/20/2020
Primal-Dual Sequential Subspace Optimization for Saddle-point Problems
We introduce a new sequential subspace optimization method for large-sca...
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02/18/2019
Low-bit Quantization of Neural Networks for Efficient Inference
Recent breakthrough methods in machine learning make use of increasingly...
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05/28/2018
Deep Discriminative Latent Space for Clustering
Clustering is one of the most fundamental tasks in data analysis and mac...
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02/13/2018
Deep Learning for Decoding of Linear Codes - A Syndrome-Based Approach
We present a novel framework for applying deep neural networks (DNN) to ...
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07/07/2017
Sparse Approximation of 3D Meshes using the Spectral Geometry of the Hamiltonian Operator
The discrete Laplace operator is ubiquitous in spectral shape analysis, ...
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11/07/2016
Hamiltonian operator for spectral shape analysis
Many shape analysis methods treat the geometry of an object as a metric ...
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09/18/2016