www.reddit.com/r/agency/comments/1jpcit8/three_digital_marketing_agencies_181_clients_6myr/
I started an agency over a decade ago with no clients, no team, and no clue. Just me, a laptop, a cell phone, and my dining room table. Today, I own three niche digital marketing agencies, generate o...
arxiv.org/abs/1401.5840v2
InAs/GaSb and similar materials systems have generated great interest as a heterojunction for tunnel field effect transistors (TFETs) due to favorable band alignment. However, little is currently understood about how such TFETs are affected by materi...
arxiv.org/abs/2401.03166v1
Variational Autoencoders (VAEs) are powerful generative models, however their generated samples are known to suffer from a characteristic blurriness, as compared to the outputs of alternative generating techniques. Extensive research efforts have bee...
github.com/hezhijie0327/GFWList2AGH
Generate diversion list for AdGuard Home and other softwares (⭐ 255)
arxiv.org/abs/2503.20089v1
We present MatplotAlt, an open-source Python package for easily adding alternative text to Matplotlib figures. MatplotAlt equips Jupyter notebook authors to automatically generate and surface chart descriptions with a single line of code or command,...
arxiv.org/abs/1303.6257v2
An algorithm for sampling exactly from the normal distribution is given. The algorithm reads some number of uniformly distributed random digits in a given base and generates an initial portion of the representation of a normal deviate in the same bas...
arxiv.org/abs/2405.08459v1
Afriat's Theorem (1967) states that a dataset can be thought of as being generated by a consumer maximizing a continuous and increasing utility function if and only if it is free of revealed preference cycles containing a strict relation. The latter...
www.bing.com/ck/a?!&&p=5fea35b5f6e02b4bbc034fcd655e8e32e06c8cbd4a576987a8eff70e62ac3dd3JmltdHM9MTc3MjQ5NjAwMA&ptn=3&ver=2&hsh=4&fclid=30cf23e3-b8c5-6928-086f-34f2b91868da&u=a1aHR0cHM6Ly9sLmZhY2Vib29rLmNvbS9mYWNlYm9vay8&ntb=1
Update! Now you can make your Facebook profile pic move ? Head over to our story to see how to generate yours.
arxiv.org/abs/2410.16785v2
Recent MIDI-to-audio synthesis methods using deep neural networks have successfully generated high-quality, expressive instrumental tracks. However, these methods require MIDI annotations for supervised training, limiting the diversity of instrument...
arxiv.org/abs/2009.09234v1
We present a system for real-time lyrical improvisation between a human and a robot in the style of hip hop. Our system takes vocal input from a human rapper, analyzes the semantic meaning, and generates a response that is rapped back by a robot over...
arxiv.org/abs/2501.10212v1
Content generation and manipulation approaches based on deep learning methods have seen significant advancements, leading to an increased need for techniques to detect whether an image has been generated or edited. Another area of research focuses on...
arxiv.org/abs/1302.5683v3
The novel STEVE (i.e., Space-Time-Enclosing Volume Extraction) algorithm is described here for the very first time. It generates iso-valued hypersurfaces that may be implicitly contained in four-dimensional (4D) data sets, such as temporal sequences...
arxiv.org/abs/2108.13327v4
Current news datasets merely focus on text features on the news and rarely leverage the feature of images, excluding numerous essential features for news classification. In this paper, we propose a new dataset, N24News, which is generated from New Yo...
arxiv.org/abs/cs/0402022v1
We present an approach to automatically generate interfaces supporting personalized interaction with digital libraries; these interfaces augment the user-DL dialog by empowering the user to (optionally) supply out-of-turn information during an inte...
arxiv.org/abs/2508.12290v1
The recent growth of large foundation models that can easily generate pseudo-labels for huge quantity of unlabeled data makes unsupervised Zero-Shot Cross-Domain Image Retrieval (UZS-CDIR) less relevant. In this paper, we therefore turn our attention...
arxiv.org/abs/2310.12971v1
The evaluation of machine-generated image captions poses an interesting yet persistent challenge. Effective evaluation measures must consider numerous dimensions of similarity, including semantic relevance, visual structure, object interactions, capt...
arxiv.org/abs/2409.12962v2
The Automated Audio Captioning (AAC) task asks models to generate natural language descriptions of an audio input. Evaluating these machine-generated audio captions is a complex task that requires considering diverse factors, among them, auditory sce...
arxiv.org/abs/2501.13309v1
We propose a dense insight network framework to encode the relationships between automatically generated insights from a complex dashboard based on their shared characteristics. Our insight network framework includes five high-level categories of rel...
en.wikipedia.org/wiki/Creative_visualization
"creative visualization" signifies the process by which a person generates and processes visual mental imagery specifically. However, creative visualization is
arxiv.org/abs/2209.08834v2
We develop NL2INTERFACE to explore the potential of generating usable interactive multi-visualization interfaces from natural language queries. With NL2INTERFACE, users can directly write natural language queries to automatically generate a fully int...