1 citations · 1 across the 8 of their papers we have counts for
11 papers
Quantitative Trading using Deep Q Learning
Soumyadip Sarkar
Reinforcement learning (RL) is a subfield of machine learning that has been used in many fields, such as robotics, gaming, and autonomous systems. There has been growing interest i…
Quantum Generative Modeling using Parameterized Quantum Circuits
Soumyadip Sarkar
Quantum generative models use the intrinsic probabilistic nature of quantum mechanics to learn and reproduce complex probability distributions. In this paper, we present an impleme…
Mining the online infosphere: A survey
Sayantan Adak, Souvic Chakraborty, Paramtia Das +7
The evolution of AI-based system and applications had pervaded everyday life to make decisions that have momentous impact on individuals and society. With the staggering growth of…
NwQM: A neural quality assessment framework for Wikipedia
Bhanu Prakash Reddy, Sasi Bhusan, Soumya Sarkar +1
Millions of people irrespective of socioeconomic and demographic backgrounds, depend on Wikipedia articles everyday for keeping themselves informed regarding popular as well as obs…
StRE: Self Attentive Edit Quality Prediction in Wikipedia
Soumya Sarkar, Bhanu Prakash Reddy, Sandipan Sikdar +1
Wikipedia can easily be justified as a behemoth, considering the sheer volume of content that is added or removed every minute to its several projects. This creates an immense scop…
On Rich Clubs of Path-Based Centralities in Networks
Soumya Sarkar, Animesh Mukherjee, Sanjukta Bhowmick
Many scale-free networks exhibit a rich club structure, where high degree vertices form tightly interconnected subgraphs. In this paper, we explore the emergence of rich clubs in t…
Core2Vec: A core-preserving feature learning framework for networks
Soumya Sarkar, Aditya Bhagwat, Animesh Mukherjee
Recent advances in the field of network representation learning are mostly attributed to the application of the skip-gram model in the context of graphs. State-of-the-art analogues…
Using Core-Periphery Structure to Predict High Centrality Nodes in Time-Varying Networks
Soumya Sarkar, Sandipan Sikdar, Animesh Mukherjee +1
Vertices with high betweenness and closeness centrality represent influential entities in a network. An important problem for time varying networks is to know a-priori, using minim…
ComPAS: Community Preserving Sampling for Streaming Graphs
Sandipan Sikdar, Tanmoy Chakraborty, Soumya Sarkar +2
In the era of big data, graph sampling is indispensable in many settings. Existing sampling methods are mostly designed for static graphs, and aim to preserve basic structural prop…
Understanding Stability of Noisy Networks through Centrality Measures and Local Connections
Vladimir Ufimtsev, Soumya Sarkar, Animesh Mukherjee +1
Networks created from real-world data contain some inaccuracies or noise, manifested as small changes in the network structure. An important question is whether these small changes…
Sensitivity and Reliability in Incomplete Networks: Centrality Metrics to Community Scoring Functions
Soumya Sarkar, Sanjukta Bhowmick, Suhansanu Kumar +1
Network analysis is an important tool in understanding the behavior of complex systems of interacting entities. However, due to the limitations of data gathering technologies, some…