Zobrazeno 1 - 10
of 1 442
pro vyhledávání: '"Sudhakaran, P"'
Autor:
Lingenberg, Tobias, Reuter, Markus, Sudhakaran, Gopika, Gojny, Dominik, Roth, Stefan, Schaub-Meyer, Simone
Simple data augmentation techniques, such as rotations and flips, are widely used to enhance the generalization power of computer vision models. However, these techniques often fail to modify high-level semantic attributes of a class. To address this
Externí odkaz:
http://arxiv.org/abs/2408.14584
The Connections puzzle is a word association game published daily by The New York Times (NYT). In this game, players are asked to find groups of four words that are connected by a common theme. While solving a given Connections puzzle requires both s
Externí odkaz:
http://arxiv.org/abs/2407.11240
Autor:
Nisioti, Eleni, Glanois, Claire, Najarro, Elias, Dai, Andrew, Meyerson, Elliot, Pedersen, Joachim Winther, Teodorescu, Laetitia, Hayes, Conor F., Sudhakaran, Shyam, Risi, Sebastian
Large Language Models (LLMs) have taken the field of AI by storm, but their adoption in the field of Artificial Life (ALife) has been, so far, relatively reserved. In this work we investigate the potential synergies between LLMs and ALife, drawing on
Externí odkaz:
http://arxiv.org/abs/2407.09502
Two fundamental challenges face generative models in engineering applications: the acquisition of high-performing, diverse datasets, and the adherence to precise constraints in generated designs. We propose a novel approach combining optimization, co
Externí odkaz:
http://arxiv.org/abs/2405.09997
Autor:
Shindo, Hikaru, Brack, Manuel, Sudhakaran, Gopika, Dhami, Devendra Singh, Schramowski, Patrick, Kersting, Kristian
Large-scale, pre-trained neural networks have demonstrated strong capabilities in various tasks, including zero-shot image segmentation. To identify concrete objects in complex scenes, humans instinctively rely on deictic descriptions in natural lang
Externí odkaz:
http://arxiv.org/abs/2402.14123
The gameplay of strategic board games such as chess, Go and Hex is often characterized by combinatorial, relational structures -- capturing distinct interactions and non-local patterns -- and not just images. Nonetheless, most common self-play reinfo
Externí odkaz:
http://arxiv.org/abs/2311.13414
Federated learning is a technique of decentralized machine learning. that allows multiple parties to collaborate and learn a shared model without sharing their raw data. Our paper proposes a federated learning framework for intrusion detection in Int
Externí odkaz:
http://arxiv.org/abs/2311.13800
Recent years have seen a growing interest in Scene Graph Generation (SGG), a comprehensive visual scene understanding task that aims to predict entity relationships using a relation encoder-decoder pipeline stacked on top of an object encoder-decoder
Externí odkaz:
http://arxiv.org/abs/2308.09472
Biological nervous systems are created in a fundamentally different way than current artificial neural networks. Despite its impressive results in a variety of different domains, deep learning often requires considerable engineering effort to design
Externí odkaz:
http://arxiv.org/abs/2307.08197
Rational control over the periodic arrangement of particles by means of external stimuli is a technologically important aspect of colloidal science with important physical underpinnings. Here, a robust structural control of particle assemblies in a n
Externí odkaz:
http://arxiv.org/abs/2304.07992