Unsupervised domain adaptation has garnered a great amount of attention and research in past decades. Among all the deep-based methods, the autoencoder-based approach has achieved sound performance for its fast convergence speed and a no-label requirement. The existing methods of autoencoders just serially connect the features generated by different autoencoders, which poses challenges for discriminative representation learning and which fails to find the real cross-domain features.Unsupervised domain adaptation has garnered a great amount of attention and research in past decades. Among all the deep-based methods, the autoencoder-based approach has achieved sound performance for its fast convergence speed and a no-label requirement. The existing methods of autoencoders just serially connect the features generated by different autoencoders, which poses challenges for discriminative representation learning and which fails to find the real cross-domain features.[#item_full_content]

Distributed cloud storage is a hot topic for security researchers around the globe pursuing secure data storage, and a team in China is now merging quantum physics with mature cryptography and storage techniques to achieve a cost-effective cloud storage solution.Distributed cloud storage is a hot topic for security researchers around the globe pursuing secure data storage, and a team in China is now merging quantum physics with mature cryptography and storage techniques to achieve a cost-effective cloud storage solution.[#item_full_content]

In the past year, AI image generators have experienced unprecedented popularity. With just a few clicks, all kinds of images can be created: even dehumanizing imagery and hate memes can be included. CISPA researcher Yiting Qu from the team of CISPA Faculty Dr. Yang Zhang has now investigated the proportion of these images among the most popular AI image generators and how their creation can be prevented with effective filters.In the past year, AI image generators have experienced unprecedented popularity. With just a few clicks, all kinds of images can be created: even dehumanizing imagery and hate memes can be included. CISPA researcher Yiting Qu from the team of CISPA Faculty Dr. Yang Zhang has now investigated the proportion of these images among the most popular AI image generators and how their creation can be prevented with effective filters.[#item_full_content]

Which drug molecule is most effective? Researchers are feverishly searching for efficient active substances to combat diseases. These compounds often dock onto proteins, which usually are enzymes or receptors that trigger a specific chain of physiological actions.Which drug molecule is most effective? Researchers are feverishly searching for efficient active substances to combat diseases. These compounds often dock onto proteins, which usually are enzymes or receptors that trigger a specific chain of physiological actions.[#item_full_content]

In the rapidly emerging world of large-scale computing, it was just a matter of time before a game-changing achievement was poised to shake up the field of 3D visualizations.In the rapidly emerging world of large-scale computing, it was just a matter of time before a game-changing achievement was poised to shake up the field of 3D visualizations.[#item_full_content]

Face recognition technology emulates human performance and can even exceed it. And it is becoming increasingly more common for it to be used with cameras for real-time recognition, such as to unlock a smartphone or laptop, log into a social media app, and to check in at the airport.Face recognition technology emulates human performance and can even exceed it. And it is becoming increasingly more common for it to be used with cameras for real-time recognition, such as to unlock a smartphone or laptop, log into a social media app, and to check in at the airport.[#item_full_content]

Deep neural networks (DNNs) have proved to be highly promising tools for analyzing large amounts of data, which could speed up research in various scientific fields. For instance, over the past few years, some computer scientists have trained models based on these networks to analyze chemical data and identify promising chemicals for various applications.Deep neural networks (DNNs) have proved to be highly promising tools for analyzing large amounts of data, which could speed up research in various scientific fields. For instance, over the past few years, some computer scientists have trained models based on these networks to analyze chemical data and identify promising chemicals for various applications.[#item_full_content]

From vehicle collision avoidance to airline scheduling systems to power supply grids, many of the services we rely on are managed by computers. As these autonomous systems grow in complexity and ubiquity, so too could the ways in which they fail.From vehicle collision avoidance to airline scheduling systems to power supply grids, many of the services we rely on are managed by computers. As these autonomous systems grow in complexity and ubiquity, so too could the ways in which they fail.[#item_full_content]

A quick scan of the headlines makes it seem like generative artificial intelligence is everywhere these days. In fact, some of those headlines may actually have been written by generative AI, like OpenAI’s ChatGPT, a chatbot that has demonstrated an uncanny ability to produce text that seems to have been written by a human.A quick scan of the headlines makes it seem like generative artificial intelligence is everywhere these days. In fact, some of those headlines may actually have been written by generative AI, like OpenAI’s ChatGPT, a chatbot that has demonstrated an uncanny ability to produce text that seems to have been written by a human.[#item_full_content]

The state space explosion problem means that the state space of Petri nets (PNs) grows exponentially with PNs’ size. Even the fundamental reachability problem is still an NP-Hard problem in general. It has been proved that the equivalence problem for the reachability set of arbitrary PNs is undecidable except for some subclass of PNs. That is, the reachability problem of arbitrary PNs cannot be solved exactly. Nowadays, there is no efficient and accurate algorithm to solve the problem.The state space explosion problem means that the state space of Petri nets (PNs) grows exponentially with PNs’ size. Even the fundamental reachability problem is still an NP-Hard problem in general. It has been proved that the equivalence problem for the reachability set of arbitrary PNs is undecidable except for some subclass of PNs. That is, the reachability problem of arbitrary PNs cannot be solved exactly. Nowadays, there is no efficient and accurate algorithm to solve the problem.[#item_full_content]