GMRES: or how to do fast linear algebra
Linear least-squares system pop up everywhere, and there are many fast way to solve them. We’ll be looking at one such way: GMRES.
It goes without saying that 2020 is a special year in a number of ways. I want to look back at what 2020 meant for me in terms of music. As a side effect of staying home almost all year, I have also listened to more music than previous years. In fact, I listened to music roughly twice as much in 2020 compared to 2019, although it still can’t match my high school levels. Below is a bar plot of my number of last.fm scrobbles since 2010.
On a less positive note, 2020 is also the year Google Play Music stopped. I’m very sad about this, as it had both great streaming features and allowed you to listen to your own uploaded music seamlessly. YouTube music is not a good replacement, so I switched to Spotify. This still leaves a lot to be desired, since I can’t add my own music to the Spotify library and listening to any music that’s not in the Spotify library is a hassle. On the plus side, Spotify does have a larger collection of music than Google Play Music did.
In the rest of this post I want to look back on the music I discovered during 2020. There has been a lot of great music that came out this year, but also a lot of music that was released before 2020 that I only discovered this year. This is not a complete list, but rather a list of the albums that had the most impact on me in no particular order. This list was compiled by looking at all the albums I listened much more than in all other years combined. I have listened to some of these albums before 2020, but I didn’t really get into them before. Let us start with the albums that were actually released this year.
Genre: Art Pop
This is definitely the album of the year for me. I can’t quite put my finger on why, but this album
just sounds amazing. I think it’s the overall sound of the album that really draws me in, and it
doesn’t become boring even after dozens of listens.
Genre: Noise Rock
Definitely one of the weirder albums of this year. At times intense, at times hypnotic and at other
times very calm. The album transitions between different moods very smoothly and results a coherent
interesting piece of music.
Genre: Post-Punk
Calm, melancholic and noisy. The texture and sound of this album is great, and just gets better
every time you listen to it.
Genre: Pop Punk
Very energetic, although the latter half of the album is very melancholic. The lyrics are also very
witty, and the noisy guitar riffs are nice, but in the end I think I like it because it’s just a
really catchy record.
Genre: Art/Baroque Pop
Probably the first French-language pop I have to come to enjoy, and probably the second best album
that came out this year as far as I’m concerned. The instrumentals on this record are perfect, and
the melody is incredibly catchy.
Genre: Dance Punk
This record sounds a lot like Talking Heads’ Remain in the Light, and this is not a bad thing.
Genre: Indie Folk
The “music video” of this album is a 45 minute video showing photographs, and I was glued to my
screen every second of it. The sound is repetitive, and it draws you in; hypnotizes you. On top of
that, it is almost as packed with emotion as A Crow Looked At Me.
Genre: Singer/Songwriter, Experimental Rock
I’m surprised I only discovered Tom Waits this year. Waits’ deep smoky voice and bluesy songs are
wonderful. It’s hard to pin this record down to a single genre, yet the sound is completely
coherent.
Genre: Slowcore
Slow, noisy and hypnotic. This album will calmly you put you into a trance, but never leave you
bored.
Genre: Math Rock
Very complex and technical instrumental math rock. Often I lose interest in purely instrumental albums
after a couple listens, but this album definitely stays interesting even after many listens.
Genre: Música Popular Brasileira
This is my first exposure to Brazillian music. After discovering this album I tried a number of
other albums in the same genre, but nothing comes close to this.
Genre: Post-Punk
I have been aware of this album for a long time, since I used to browse /mu/ in high school, but I
only really got into it this year. The album is very intense, and I simply love the lo-fi sound of
the record.
Genre: Post-Hardcore, Math Rock
Beautiful, noisy sound. Reminds me a lot of Number Girl, but with a much stronger beat. It’s hard
not to bop my head to this.
Genre: Post-Punk
Incredibly energetic punk. It takes a very wholesome spin on the traditional anarchistic lyrics of
punk rock. IDLES also released an album in 2020, and while it’s certainly good, it didn’t leave
nearly as much as an impression on me as this album.
Genre: Alt-Country
Country rock meets existential dread.
Genre: Sludge Metal
Like Melvins’ or Boris’ Sludge Metal records, but much more raw and dark. I love it.
Genre: Hardcore Punk
The lyrics are a bit angsty, but the dark, raw, noisy sound more than makes up for that.
Genre: Industrial Hip-Hop, Horrorcore
This is probably the biggest surprise for me this year. I didn’t expect to like
this at all, but I really do. For some reason I find it difficult to like hip-hop, especially rap.
Perhaps the noisy sound of this album is what attracts me to it.
Genre: Indie Rock
A lo-fi indie pop, but still definitely sounds like the 90s, and definitely holds up against some of
the best albums of that decade.
Genre: Neofolk
A sombre, melancholic, acoustic album. At first I didn’t like this album, but a few months after
listening to this album for a few times several songs got stuck into my head. I then listened to the
album again and found that I suddenly really enjoyed it.
Genre: Progressive Folk, Freak Folk
Grim, psychedelic and intense. The album draws you in, despite its dark and disturbing content.
Genre: Psychedelic Folk
Psychedelic, yet calm and relaxing. Probably my first exposure to Korean music (other than k-pop),
and I definitely want to hear more of this.
Linear least-squares system pop up everywhere, and there are many fast way to solve them. We’ll be looking at one such way: GMRES.
We recently made a paper about supervised machine learning using tensors, here’s the gist of how this works.
A lot of data is naturally of ‘low rank’. I will explain what this means, and how to exploit this fact.
Parsing and editing Word documents automatically can be extremely useful, but doing it in Python is not that straightforward.
Finally, let’s look at how we can automatically sharpen images, without knowing how they were blurred in the first place.
Deconvolving and sharpening images is actually pretty tricky. Let’s have a look at some more advanced methods for deconvolution.
In order to automatically sharpen images, we need to first understand how a computer can judge how ‘natural’ an image looks.
Deconvolution is one of the cornerstones of image processing. Let’s take a look at how it works.