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Market Intel Report by Chainalysis gives you the unique insights you need to make cryptocurrency research and investment decisions. Every week our Chief Economist, Philip Gradwell, explores our Market Intel dataset to explain the events and trends on the blockchain that drive cryptocurrency markets. Be sure to subscribe to get the weekly Market Intel Report delivered to your inbox. Visit https://markets.chainalysis.com/ to view live data and read past reports. - Keep up with Philip: https:// ...
 
BrainPod is the podcast from the journal Neuropsychopharmacology, produced in association with Nature Publishing Group. Join us as we delve into the latest basic and clinical research that advance our understanding of the brain and behavior, featuring highlighted content from a top journal in fields of neuroscience, psychiatry, and pharmacology. For complete access to the original papers and reviews featured in this podcast, subscribe to Neuropsychopharmacology.
 
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iCritical Care: All Audio

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iCritical Care: All Audio

Society of Critical Care Medicine (SCCM)

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iCritical Care: All Audio offers access to all of the Society of Critical Care Medicine's podcasts offering in-depth interviews on adult and pediatric clinical topics as well as updates in the field on various issues. Subscribing to All Audio ensures you receive all podcasts, whether iCritical Care hosts are chatting with authors from the Critical Care Medicine and Pediatric Critical Care Medicine journals, or covering other important topics with well-known speakers, prominent SCCM members o ...
 
Deep Learning (DL) has attracted much interest in a wide range of applications such as image recognition, speech recognition and artificial intelligence, both from academia and industry. This lecture introduces the core elements of neural networks and deep learning, it comprises: (multilayer) perceptron, backpropagation, fully connected neural networks loss functions and optimization strategies convolutional neural networks (CNNs) activation functions regularization strategies common practic ...
 
Keeping you up to date with the latest trends and best performing architectures in this fast evolving field in computer science. Selecting papers by comparative results, citations and influence we educate you on the latest research. Consider supporting us on Patreon.com/PapersRead for feedback and ideas.
 
Using cultivars’ proprietary machine learning and AI technology, we are able to analyze real-time pictures and within seconds and scan our extensive cannabis dataset to give you a diagnosis of the health of your plant as well as consultation on how to improve yield and quality. Cultivars will generate a personal portfolio to track your progress with all of your plants. It will be able to identify various conditions such as the stage of growth, and subsequent nutritional needs. Our technology ...
 
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PlanIt

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PlanIt

Metropolitan Council

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The PlanIt Podcast is the new part of the 2017 PlanIt Training Program on Comprehensive Plan Updates. This series will feature monthly episodes on a variety of topics that are not required elements of a comprehensive plan through conversations with planning experts and professionals outside of the Metropolitan Council.
 
The Abbot of the Space-Anchor of Logic (S-AoL) speaks publicly for the first time since the S-AoL came into existence in November of 2018, connecting the Earth and Mars via a divine geometrical construction, thereby preparing the way for Einstein's "god" to defeat Entropy in the Universe and grant our community eternal life.
 
The Royal Statistical Society (RSS) is one of the world's most distinguished and renowned statistical societies. It is a learned society for statistics, a professional body for statisticians and a charity which promotes statistics, data and evidence for the public good. It was founded in 1834 as the Statistical Society of London and became the Royal Statistical Society by Royal Charter in 1887. Today the Society has more than 10,000 members around the world, of whom many are professionally q ...
 
Humans in the Loop sheds a light on thought leaders in various verticals of data science, machine learning, and artificial intelligence. Once every two weeks, we share our interviews with leading experts from around the world, where we explore how solving a machine and deep learning problem helps achieve business goals and foster innovation. Tune in to stay in the loop with the latest groundbreaking ideas on the AI/ML landscape. You can shape this podcast by helping us pick our next guest by ...
 
De Nog Even Over... podcast heeft geen vast onderwerp of thema, maar gaat over alles dat kan volgen op "nog even over..." dat op een manier mijn interesse heeft gewekt. Ik, Bas Keetelaar, ben 23 jaar en afgestudeerd als interaction designer en heb passie voor technologie, design, games en gadgets.
 
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Adverse Reactions

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Adverse Reactions

Anne Chappelle, PhD, and David Faulkner, PhD

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An interview podcast bringing you the people and stories behind the science of how biological, physical, and chemical agents may cause adverse reactions to public, animal, and environmental health. This podcast is presented by the Society of Toxicology (SOT) and hosted by SOT members Anne Chappelle and David Faulkner. About Anne After graduating from the University of Delaware with a BS in biology in 1991, Anne Chappelle accidentally found her calling when she worked a gap year in an industr ...
 
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show series
 
The scale, variety, and quantity of publicly available NLP datasets has grown rapidly as researchers propose new tasks, larger models, and novel benchmarks. Datasets is a community library for contemporary NLP designed to support this ecosystem. 2021: Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, A. Thakur, Patrick von Platen, Suraj P…
 
Dan Quintana is a senior researcher at the University of Olso, where his research focuses on oxytocin, autism, and meta-analyses. In this conversation, we talk about Dan's primer on synthetic datasets, science comunication, Everything Hertz, and podcasting in general. BJKS Podcast is a podcast about neuroscience, psychology, and anything vaguely re…
 
Overview: Today, we’re going to have a creator roundtable to discuss the African tech ecosystem. We’ll discuss the biggest 2021 moments in Africa Tech and our hopes for the ecosystem in 2022. This episode was co-hosted with Justin Norman & Samora Kariuku and recorded on Nov 28, 2021. Companies discussed: Adamantium Fund, Wave, Sendwave, Andela, Flu…
 
This is the first episode of a book club series on Peter Gärdenfors's book Conceptual Spaces. In this episode, we will discuss chapters 1 and 2, which provide an overview over the book, and a discussion of the three kinds of representation: subconceptual, conceptual, and symbolic. For this series, I'm joined by Koen Frolichcs, who was already my co…
 
Transformers have shown great potential in computer vision tasks. A common belief is their attention-based token mixer module contributes most to their competence. However, recent works show the attention-based module in transformers can be replaced by spatial MLPs and the resulted models still perform quite well. Based on this observation, we hypo…
 
Deploying Machine Learning (ML) algorithms within databases is a challenge due to the varied computational footprints of modern ML algorithms and the myriad of database technologies each with their own restrictive syntax. We introduce an Apache Spark-based micro-service orchestration framework that extends database operations to include web service…
 
Timestamps (02:13) Prukalpa discussed her upbringing in India and studying Engineering at the Nanyang Tech University in Singapore. (03:52) Prukalpa shared the key learnings from her summer internship as an Investment Banking Analyst at Goldman Sachs. (05:37) Prukalpa went over the seed idea for SocialCops (Read her Quora answer on the fundraising …
 
Successful quantitative investment usually relies on precise predictions of the future movement of the stock price. Recently, machine learning based solutions have shown their capacity to give more accurate stock prediction and become indispensable components in modern quantitative investment systems. However, the i.i.d. assumption behind existing …
 
Vision transformer (ViT) has recently showed its strong capability in achieving comparable results to convolutional neural networks (CNNs) on image classification. However, vanilla ViT simply inherits the same architecture from the natural language processing directly, which is often not optimized for vision applications. Motivated by this, in this…
 
Michael Hornberger is a professor of applied dementia research who developed Sea Hero Quest, a mobile game for studying spatial navigation that was downloaded more than 4 million times. In this conversation, we talk about Sea Hero Quest, how Michael (together with Hugo Spiers) developed it, the first findings, and dementia in general. BJKS Podcast …
 
Remotely sensed geospatial data are critical for applications including precision agriculture, urban planning, disaster monitoring and response, and climate change research, among others. 2021: Adam J. Stewart, Caleb Robinson, Isaac A. Corley, Anthony Ortiz, Juan M. Lavista Ferres, Arindam Banerjeehttps://arxiv.org/pdf/2111.08872v1.pdf…
 
When engineers train deep learning models, they are very much “flying blind”. Commonly used approaches for realtime training diagnostics, such as monitoring the train/test loss, are limited. Assessing a network’s training process solely through these performance indicators is akin to debugging software without access to internal states through a de…
 
Overview: Today, we’re going to talk about Andela - the software developer recruitment platform. We’ll explore the Andela story across 6 areas: Labor markets in Africa context Andela's founding and early history Fundraising & Growth Product & monetization strategy Competitive positioning & potential exit options Overall outlook. This episode was co…
 
Transformer-based models consist of interleaved feed-forward blocks - that capture content meaning, and relatively more expensive self-attention blocks - that capture context meaning. In this paper, we explored trade-offs and ordering of the blocks to improve upon the current Transformer architecture and proposed PAR Transformer. 2020: Swetha Manda…
 
Knowledge-based visual question answering (VQA) involves answering questions that require external knowledge not present in the image. Inspired by GPT-3’s power in knowledge retrieval and question answering, instead of using structured KBs as in previous work, we treat GPT-3 as an implicit and unstructured KB that can jointly acquire and process re…
 
We present FastPitch, a fully-parallel text-to-speech model based on FastSpeech, conditioned on fundamental frequency contours. The model predicts pitch contours during inference, and generates speech that could be further controlled with predicted contours. FastPitch can thus change the perceived emotional state of the speaker or put emphasis on c…
 
All communities have to deal with parking requirements. These requirements can at times impose tremendous limitations on developments. Considering the wide impact that parking requirements can have on future of development, many communities have undertaken efforts to reform them. Additionally, with changes in parking demand and driving habits, as w…
 
Dawn Zoldi of P3 Tech Consulting explains her journey from JAG lawyer for the U.S. Air Force to creating policies on domestic use of military drones in the U.S. national airspace. After winning the Woman to Watch and UAS Global award, she was inspired to create her company, P3 Tech Consulting. Dawn discusses that her primary focus is on education a…
 
Transformer emerges as a powerful tool for visual recognition. In addition to demonstrating competitive performance on a broad range of visual benchmarks, recent works also argue that Transformers are much more robust than Convolutions Neural Networks (CNNs). Nonetheless, surprisingly, we find these conclusions are drawn from unfair experimental se…
 
Although residual connection enables training very deep neural networks, it is not friendly for online inference due to its multi-branch topology. This encourages many researchers to work on designing DNNs without residual connections at inference. In this paper, we aim to remedy this problem and propose to remove the residual connection in a vanil…
 
We consider a new problem of adapting a human mesh reconstruction model to out-of-domain streaming videos, where performance of existing SMPL-based models are significantly affected by the distribution shift represented by different camera parameters, bone lengths, backgrounds, and occlusions. We tackle this problem through online adaptation, gradu…
 
Pretrained language models have become the standard approach for many NLP tasks due to strong performance, but they are very expensive to train. We propose a simple and efficient learning framework TLM that does not rely on large-scale pretraining1. Given some labeled task data and a large general corpus, TLM uses task data as queries to retrieve a…
 
When should clinicians intubate preterm infants? The answer is not always straightforward, according to podcast guest Deepak Jain, MD, FAAP. He and host Pamela M. Peeke, MD, MPH, FACP, FACSM, discuss strategies that optimize noninvasive ventilation and when such strategies are appropriate.By The Society of Critical Care Medicine (SCCM)
 
In episode 42 I interviewed Matthias Stangl about his work on spatial navigation. I wanted to ask him a few questions about postdoc applications, but we ran out of time. Matthias kindly agreed to meet again for a few questions that I would add to the end of our conversation. We ended up speaking for almost an hour, so instead of adding this to an e…
 
Segmenting medical images accurately and reliably is important for disease diagnosis and treatment. It is a challenging task because of the wide variety of objects’ sizes, shapes, and scanning modalities. Recently, many convolutional neural networks (CNN) have been designed for segmentation tasks and achieved great success. Few studies, however, ha…
 
Cutting-edge 3D face reconstruction methods use non-linear morphable face models combined with GAN-based decoders to capture the likeness and details of a person but fail to produce neutral head models with unshaded albedo textures which is critical for creating relightable and animation-friendly avatars for integration in virtual environments.2021…
 
Real-time semantic segmentation is playing a more important role in computer vision, due to the growing demand for mobile devices and autonomous driving. Therefore, it is very important to achieve a good trade-off among performance, model size and inference speed. In this paper, we propose a Channel-wise Feature Pyramid (CFP) module to balance thos…
 
Prompt-learning has become a new paradigm in modern natural language processing, which directly adapts pre-trained language models (PLMs) to cloze-style prediction, autoregressive modeling, or sequence to sequence generation, resulting in promising performances on various tasks. However, no standard implementation framework of prompt-learning is pr…
 
Neural painting refers to the procedure of producing a series of strokes for a given image and non-photo realistically recreating it using neural networks. We formulate the task as a set prediction problem and propose a novel Transformer based framework, dubbed Paint Transformer, to predict the parameters of a stroke set with a feed forward network…
 
This paper explores a simple method for improving the zero-shot learning abilities of language models. We show that instruction tuning—fine tuning language models on a collection of tasks described via instructions—substantially boosts zero-shot performance on unseen tasks. We take a 137B parameter pre trained language model and instruction-tune it…
 
This month we talk a look at provincial and national referendums in Canada. Listen to our podcast here or on Spreaker For this month’s podcast we compiled a list of all the provincial and national referendums in Canada that we could find. You would think a list like this would be easy to find, but it wasn’t. We managed to find some resources from E…
 
Matthias Stangl is a postdoc at UCLA, where he studies the neural representations of spatial navigation in social situations. In this conversation, we talk about his PhD work about aging, grid cells, and path integration, about his recent Nature paper, about the difference between movement in VR and actual physical movement, and much more. BJKS Pod…
 
Overview: Today, we’re going to talk about SafeBoda - the Ugandan motorbike hailing platform. We’ll explore the SafeBoda story across 7 areas: Motorbike hailing platforms in other emerging markets (GoJek/GoTo) African mobility context SafeBoda's founding & early history Fundraising and growth Product & monetization strategy Competitive positioning …
 
Timestamps (01:58) Michel went over his education studying at EPITA — School of Engineering and Computer Science in France. (03:50) Michel mentioned his first US internship at Siemens Corporate Research as an R&D engineer. (05:48) Michel discussed the unique challenges of building systems to handle financial data through his engineering experience …
 
Data augmentation is a simple yet effective way to improve the robustness of deep neural networks (DNNs). Diversity and hardness are two complementary dimensions of data augmentation to achieve robustness. For example, AugMix explores random compositions of a diverse set of augmentations to enhance broader coverage, while adversarial training gener…
 
Star-shaped cells called astrocytes are the most abundant cells to be found in the human brain. In the past, they’d been thought to play a supporting role to neurons, such as providing metabolic support, but recently they’re also emerging as stars of information processing. They can respond to neurotransmitters and release neuroactive substances th…
 
We propose a novel neural representation for videos (NeRV) which encodes videos in neural networks. Unlike conventional representations that treat videos as frame sequences, we represent videos as neural networks taking frame index as input. Given a frame index, NeRV outputs the corresponding RGB image. Video encoding in NeRV is simply fitting a ne…
 
Transformers have attracted increasing interests in computer vision, but they still fall behind state-of-the-art convolutional networks. In this work, we show that while Transformers tend to have larger model capacity, their generalization can be worse than convolutional networks due to the lack of the right inductive bias. To effectively combine t…
 
This is the second episode of an experiment: I'll be reviewing all books called "Prisoner's Dilemma". Today I'm reviewing The Mysterious Benedict Society and the Prisoner's Dilemma by Trenton Lee Stewart and Prisoner's Dilemma by Ilexa Yardley. BJKS Podcast is a podcast about neuroscience, psychology, and anything vaguely related, hosted by Benjami…
 
We present TWIST, a novel self-supervised representation learning method by classifying large-scale unlabeled datasets in an end-to-end way. We employ a siamese network terminated by a softmax operation to produce twin class distributions of two augmented images. Without supervision, we enforce the class distributions of different augmentations to …
 
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