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20082026
most citedTen Years of Generative Adversarial Nets (GANs): A survey of the state-of-the-art

168 citations

Showing 2021Show all

14 papers · 1 filter

cs.MA2021★ 2 cited

Modeling Prejudice and Its Effect on Societal Prosperity

Deep Inder Mohan, Arjun Verma, Shrisha Rao

Existing studies on prejudice, which is important in multi-group dynamics in societies, focus on the social-psychological knowledge behind the processes involving prejudice and its…

cs.AI2021★ 1 cited

Paradigms of Computational Agency

Srinath Srinivasa, Jayati Deshmukh

Agent-based models have emerged as a promising paradigm for addressing ever increasing complexity of information systems. In its initial days in the 1990s when object-oriented mode…

cs.CV2021

Using Topological Framework for the Design of Activation Function and Model Pruning in Deep Neural Networks

Yogesh Kochar, Sunil Kumar Vengalil, Neelam Sinha

Success of deep neural networks in diverse tasks across domains of computer vision, speech recognition and natural language processing, has necessitated understanding the dynamics…

cs.CV2021

Towards Learning a Vocabulary of Visual Concepts and Operators using Deep Neural Networks

Sunil Kumar Vengalil, Neelam Sinha

Deep neural networks have become the default choice for many applications like image and video recognition, segmentation and other image and video related tasks.However, a critical…

cs.CV2021

One-shot domain adaptation for semantic face editing of real world images using StyleALAE

Ravi Kiran Reddy, Kumar Shubham, Gopalakrishnan Venkatesh +4

Semantic face editing of real world facial images is an important application of generative models. Recently, multiple works have explored possible techniques to generate such modi…

cs.CY2021★ 1 cited

Connecting the Dots in Nutritional Rehabilitation: A Qualitative Study on ICT and Community Based Care

Deepa Austin, Amit Prakash

'Fragmentation in care' continuum is often considered as a shortcoming of Health system whereas, 'Integration of care' is widely acclaimed as a viable solution to fragmentation. In…

cs.AR2021

Analysing digital in-memory computing for advanced finFET node

Veerendra S Devaraddi, Joycee M. Mekie

Digital In-memory computing improves energy efficiency and throughput of a data-intensive process, which incur memory thrashing and, resulting multiple same memory accesses in a vo…

cs.NI2021

Predictive Dynamic Scaling Multi-Slice-in-Slice-Connected Users for 5G System Resource Scheduling

Sharvari Ravindran, Saptarshi Chaudhuri, Jyotsna Bapat +1

Network slicing is an effective 5G concept for improved resource utilization and service scalability tailored to users (UEs) requirements. According to the standardization, 5G syst…

cs.NI2021★ 4 cited

Optimization Results for 5G Slice-in-Slice Scheduling

Sharvari Ravindran, Saptarshi Chaudhuri, Jyotsna Bapat +1

Open Radio Access Network (ORAN) Slicing for 5G and Beyond is an emerging architecture and feature that will facilitate challenging RAN Service Level Agreement (SLA) assurance targ…

cs.AI2021★ 40 cited

Modeling Influencer Marketing Campaigns in Social Networks

Ronak Doshi, Ajay Ramesh Ranganathan, Shrisha Rao

Social media are extensively used in today's world, and facilitate quick and easy sharing of information, which makes them a good way to advertise products. Influencers of a social…

cs.SE2021

Discovering Multiple Design Approaches in Programming Assignment Submissions

Nikhila KN, Sujit Kumar Chakrabarti, Manish Gupta

In this paper, we present a novel approach of automated evaluation of programming assignments~(AEPA) the highlight of which is that it automatically identifies multiple solution ap…

cs.CL2021★ 10 cited

Unsupervised Contextual Paraphrase Generation using Lexical Control and Reinforcement Learning

Sonal Garg, Sumanth Prabhu, Hemant Misra +1

Customer support via chat requires agents to resolve customer queries with minimum wait time and maximum customer satisfaction. Given that the agents as well as the customers can h…

cs.NI2021

A Data Augmented Bayesian Network for Node Failure Prediction in Optical Networks

Dibakar Das, Mohammad Fahad Imteyaz, Jyotsna Bapat +1

Failures in optical network backbone can cause significant interruption in internet data traffic. Hence, it is very important to reduce such network outages. Prediction of such fai…

cs.NI2021

A Non-intrusive Failure Prediction Mechanism for Deployed Optical Networks

Dibakar Das, Mohammad Fahad Imteyaz, Jyotsna Bapat +1

Failures in optical network backbone can lead to major disruption of internet data traffic. Hence, minimizing such failures is of paramount importance for the network operators. Ev…