Search Results for author: Ayan Das

Found 13 papers, 2 papers with code

A Graph Convolution Network-based System for Technical Domain Identification

no code implementations ICON 2020 Alapan Kuila, Ayan Das, Sudeshna Sarkar

This paper presents the IITKGP contribution at the Technical DOmain Identification (TechDOfication) shared task at ICON 2020.

Classification POS +1

A little perturbation makes a difference: Treebank augmentation by perturbation improves transfer parsing

no code implementations ICON 2019 Ayan Das, Sudeshna Sarkar

We present an approach for cross-lingual transfer of dependency parser so that the parser trained on a single source language can more effectively cater to diverse target languages.

Cross-Lingual Transfer

SketchODE: Learning neural sketch representation in continuous time

no code implementations ICLR 2022 Ayan Das, Yongxin Yang, Timothy Hospedales, Tao Xiang, Yi-Zhe Song

Learning meaningful representations for chirographic drawing data such as sketches, handwriting, and flowcharts is a gateway for understanding and emulating human creative expression.

Data Augmentation

Demographic noise can promote abrupt transitions in ecological systems

no code implementations29 Mar 2021 Sabiha Majumder, Ayan Das, Appilineni Kushal, Sumithra Sankaran, Vishwesha Guttal

In this paper, we show that demographic noise may, in fact, promote abrupt transitions in systems that would otherwise show continuous transitions.

Cloud2Curve: Generation and Vectorization of Parametric Sketches

1 code implementation CVPR 2021 Ayan Das, Yongxin Yang, Timothy Hospedales, Tao Xiang, Yi-Zhe Song

Analysis of human sketches in deep learning has advanced immensely through the use of waypoint-sequences rather than raster-graphic representations.

BézierSketch: A generative model for scalable vector sketches

1 code implementation ECCV 2020 Ayan Das, Yongxin Yang, Timothy Hospedales, Tao Xiang, Yi-Zhe Song

The study of neural generative models of human sketches is a fascinating contemporary modeling problem due to the links between sketch image generation and the human drawing process.

Image Generation

Improving cross-lingual model transfer by chunking

no code implementations27 Feb 2020 Ayan Das, Sudeshna Sarkar

We present a shallow parser guided cross-lingual model transfer approach in order to address the syntactic differences between source and target languages more effectively.

Chunking

HMM-based Indic Handwritten Word Recognition using Zone Segmentation

no code implementations1 Aug 2017 Partha Pratim Roy, Ayan Kumar Bhunia, Ayan Das, Prasenjit Dey, Umapada Pal

To avoid character segmentation in such scripts, HMM-based sequence modeling has been used earlier in holistic way.

Development of a Bengali parser by cross-lingual transfer from Hindi

no code implementations WS 2016 Ayan Das, Agnivo Saha, Sudeshna Sarkar

A parser is trained and applied to the Hindi sentences of the parallel corpus and the parse trees are projected to construct probable parse trees of the corresponding Bengali sentences.

Chunking Cross-Lingual Transfer

Distributed Weighted Parameter Averaging for SVM Training on Big Data

no code implementations30 Sep 2015 Ayan Das, Sourangshu Bhattacharya

Experimental results on a variety of toy and real world datasets show that our approach is significantly more accurate than parameter averaging for high number of partitions.

Cannot find the paper you are looking for? You can Submit a new open access paper.