Search Results for author: Sourav Medya

Found 12 papers, 6 papers with code

Global Counterfactual Explainer for Graph Neural Networks

1 code implementation21 Oct 2022 Mert Kosan, Zexi Huang, Sourav Medya, Sayan Ranu, Ambuj Singh

One way to address this is counterfactual reasoning where the objective is to change the GNN prediction by minimal changes in the input graph.

Counterfactual Explanation Graph Classification

Incorporating Heterophily into Graph Neural Networks for Graph Classification

1 code implementation15 Mar 2022 Wei Ye, Jiayi Yang, Sourav Medya, Ambuj Singh

Graph neural networks (GNNs) often assume strong homophily in graphs, seldom considering heterophily which means connected nodes tend to have different class labels and dissimilar features.

Classification Graph Classification

An Exploratory Study of Stock Price Movements from Earnings Calls

no code implementations31 Jan 2022 Sourav Medya, Mohammad Rasoolinejad, Yang Yang, Brian Uzzi

Third, the semantic features of transcripts are more predictive of stock price movements than sales and earnings per share, i. e., traditional hard data in most of the cases.

Task and Model Agnostic Adversarial Attack on Graph Neural Networks

1 code implementation25 Dec 2021 Kartik Sharma, Samidha Verma, Sourav Medya, Arnab Bhattacharya, Sayan Ranu

In this work, we study this problem and show that GNNs remain vulnerable even when the downstream task and model are unknown.

Adversarial Attack Q-Learning

A Neural Framework for Learning Subgraph and Graph Similarity Measures

1 code implementation24 Dec 2021 Rishabh Ranjan, Siddharth Grover, Sourav Medya, Venkatesan Chakaravarthy, Yogish Sabharwal, Sayan Ranu

Further, owing to its pair-independent embeddings and theoretical properties, NEUROSED allows approximately 3 orders of magnitude faster retrieval of graphs and subgraphs.

Graph Similarity Inductive Bias +1

Event Detection on Dynamic Graphs

1 code implementation23 Oct 2021 Mert Kosan, Arlei Silva, Sourav Medya, Brian Uzzi, Ambuj Singh

In this paper, we propose DyGED, a simple yet novel deep learning model for event detection on dynamic graphs.

Decision Making Event Detection

Feature-based Individual Fairness in k-Clustering

no code implementations9 Sep 2021 Debajyoti Kar, Sourav Medya, Debmalya Mandal, Arlei Silva, Palash Dey, Swagato Sanyal

Ensuring fairness in machine learning algorithms is a challenging and important task.


Meta-Learning with Graph Neural Networks: Methods and Applications

no code implementations27 Feb 2021 Debmalya Mandal, Sourav Medya, Brian Uzzi, Charu Aggarwal

Graph Neural Networks (GNNs), a generalization of deep neural networks on graph data have been widely used in various domains, ranging from drug discovery to recommender systems.

Drug Discovery Meta-Learning +1

Investigating Ground-level Ozone Formation: A Case Study in Taiwan

no code implementations18 Dec 2020 Yu-Wen Chen, Sourav Medya, Yi-Chun Chen

In this paper, we aim to identify and understand the impact of various factors on O3 formation and predict the O3 concentrations under different pollution-reduced and climate change scenarios.

Manipulating Node Similarity Measures in Networks

no code implementations25 Oct 2019 Palash Dey, Sourav Medya

These similarity measures turn out to be an important fundamental tool for many real world applications such as link prediction in networks, recommender systems etc.

Social and Information Networks Data Structures and Algorithms

Learning Heuristics over Large Graphs via Deep Reinforcement Learning

2 code implementations NeurIPS 2020 Sahil Manchanda, Akash Mittal, Anuj Dhawan, Sourav Medya, Sayan Ranu, Ambuj Singh

Additionally, a case-study on the practical combinatorial problem of Influence Maximization (IM) shows GCOMB is 150 times faster than the specialized IM algorithm IMM with similar quality.

Combinatorial Optimization Q-Learning +2

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